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Action required! Mendeley is changing its\n API. In order to keep using Mendeley with BibBase past April\n 14th, you need to:\n

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\n  \n 2016\n \n \n (8)\n \n \n
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\n \n \n\n \n \n \n \n Knowledge-driven paper retrieval from PubMed: to support updating of clinical guidelinese.\n \n\n\n \n Zamborlini, V.; Hu, Q.; Huang, Z.; da Silveira, Marcos Pruski , C.; ten Teije, A.; Van; and Harmelen, F.\n \n\n\n \n\n\n\n In Proceedings of International Joint Workshop KR4HC 2016 - ProHeath 2016 (in conjunction with HEC 2016), Munich, 2016. \n \n\n\n\n
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@inproceedings{Zamborlini2016a,\naddress = {Munich},\nauthor = {Zamborlini, Veruska and Hu, Qing and Huang, Zhisheng and {da Silveira, Marcos Pruski}, C{\\'{e}}dric and ten Teije, Annette and Van and Harmelen, Frank},\nbooktitle = {Proceedings of International Joint Workshop KR4HC 2016 - ProHeath 2016 (in conjunction with HEC 2016)},\ndoi = {10.1007/978-3-319-55014-5_5},\ntitle = {{Knowledge-driven paper retrieval from PubMed: to support updating of clinical guidelinese}},\nyear = {2016}\n}\n
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\n \n \n\n \n \n \n \n Generalizing the Detection of Internal and External Interactions in Clinical Guidelines.\n \n\n\n \n Zamborlini, V.; Hoekstra, R.; Silveira, M.; Pruski, C.; and Teije, A.\n \n\n\n \n\n\n\n In Proceedings of the 9th International Conference on Health Informatics (HEALTHINF2016), Rome, Italy, 2016. \n \n\n\n\n
\n\n\n \n \n \n \"GeneralizingPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Zamborlini2016,\naddress = {Rome, Italy},\nauthor = {Zamborlini, Veruska and Hoekstra, Rinke and Silveira, Marcos and Pruski, Cedric and Teije, Annette},\nbooktitle = {Proceedings of the 9th International Conference on Health Informatics (HEALTHINF2016)},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Zamborlini et al. - 2016 - Generalizing the Detection of Internal and External Interactions in Clinical Guidelines.pdf:pdf},\ntitle = {{Generalizing the Detection of Internal and External Interactions in Clinical Guidelines}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2016HealthInf-Zamborlini.pdf},\nyear = {2016}\n}\n
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\n \n \n\n \n \n \n \n Detecting new evidences for evidence-based medical guidelines with journal filtering.\n \n\n\n \n Qing, H.; Huang, Z.; ten Teije, A.; and Frank van Harmelen\n \n\n\n \n\n\n\n In Proceedings of International Joint Workshop KR4HC 2016 - ProHeath 2016 (in conjunction with HEC 2016), Munich, 2016. \n \n\n\n\n
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@inproceedings{Qing2016,\naddress = {Munich},\nauthor = {Qing, Hu and Huang, Zhisheng and ten Teije, Annette and {Frank van Harmelen}},\nbooktitle = {Proceedings of International Joint Workshop KR4HC 2016 - ProHeath 2016 (in conjunction with HEC 2016)},\ndoi = {10.1007/978-3-319-55014-5_8},\ntitle = {{Detecting new evidences for evidence-based medical guidelines with journal filtering}},\nyear = {2016}\n}\n
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\n \n \n\n \n \n \n \n A Topic-centric Approach to Detecting New Evidences for Evidence-based Medical Guidelines.\n \n\n\n \n Hu, Q.; Huang, Z.; Teije, A.; Harmelen, F. V.; and Marshall, M S.\n \n\n\n \n\n\n\n In Proceedings of the 9th International Conference on Health Informatics (HEALTHINF2016), Rome, Italy, 2016. \n \n\n\n\n
\n\n\n \n \n \n \"APaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Hu2016,\naddress = {Rome, Italy},\nauthor = {Hu, Qing and Huang, Zhisheng and Teije, Annette and Harmelen, Frank Van and Marshall, M Scott},\nbooktitle = {Proceedings of the 9th International Conference on Health Informatics (HEALTHINF2016)},\nfile = {:Users/annette/Dropbox/AnnetteDropBoxVU/personal/Annette-www/papers-pdf/2016HealthInf-Hu.pdf:pdf},\nkeywords = {best available evidence in,biomedical science,context-awareness,developed based on the,evidence-based medical guidelines,evidence-based medical guidelines are,medical guideline update,semantic distance,topic-centric approach},\ntitle = {{A Topic-centric Approach to Detecting New Evidences for Evidence-based Medical Guidelines}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2016HealthInf-Hu.pdf},\nyear = {2016}\n}\n
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\n \n \n\n \n \n \n \n Formalisation and automated computation of diabetes clinical quality indicators with Chinese hospital patient data.\n \n\n\n \n Haitong, L.; ten Teije, A.; Dentler, K.; Ma, J.; and Zhang, S.\n \n\n\n \n\n\n\n In Proceedings of International Joint Workshop KR4HC 2016 - ProHeath 2016 (in conjunction with HEC 2016), Munich, 2016. \n \n\n\n\n
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@inproceedings{Haitong2016,\naddress = {Munich},\nauthor = {Haitong, Liu and ten Teije, Annette and Dentler, Kathrin and Ma, Jingdong and Zhang, Shijing},\nbooktitle = {Proceedings of International Joint Workshop KR4HC 2016 - ProHeath 2016 (in conjunction with HEC 2016)},\ndoi = {https://doi.org/10.1007/978-3-319-55014-5_2},\ntitle = {{Formalisation and automated computation of diabetes clinical quality indicators with Chinese hospital patient data}},\nyear = {2016}\n}\n
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\n \n \n\n \n \n \n \n A Task-based Comparison of Linguistic and Semantic Document Retrieval Methods in the Medical Domain.\n \n\n\n \n Shafahi, M.; Qing, H.; Afsarmanesh, H.; Huang, Z.; ten Teije, A.; and van Harmelen, F.\n \n\n\n \n\n\n\n In 1st International Workshop on Extraction and Processing of Rich Semantics from Medical Texts (ESWC 2016 Workshop), 2016. \n \n\n\n\n
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@inproceedings{Shafahi2016,\nauthor = {Shafahi, Mohammad and Qing, Hu and Afsarmanesh, Hamideh and Huang, Zhisheng and ten Teije, Annette and van Harmelen, Frank},\nbooktitle = {1st International Workshop on Extraction and Processing of Rich Semantics from Medical Texts (ESWC 2016 Workshop)},\ntitle = {{A Task-based Comparison of Linguistic and Semantic Document Retrieval Methods in the Medical Domain}},\nyear = {2016}\n}\n
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\n \n \n\n \n \n \n \n Predictive modeling of colorectal cancer using a dedicated pre-processing pipeline on routine electronic medical.\n \n\n\n \n Kop, R.; Hoogendoorn, M.; ten Teije, A.; Büchner, Frederike L Slottje, P.; Moons, L. M.; and Numans, M. E.\n \n\n\n \n\n\n\n Computers in Biology and Medicine, 76: 30--38. 2016.\n \n\n\n\n
\n\n\n \n \n \n \"PredictivePaper\n  \n \n\n \n \n doi\n  \n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@article{Kop2016,\nabstract = {Over the past years, research utilizing routine care data extracted from Electronic Medical Records (EMRs) has increased tremendously. Yet there are no straightforward, standardized strategies for pre-processing these data. We propose a dedicated medical pre-processing pipeline aimed at taking on many problems and opportunities contained within EMR data, such as their temporal, inaccurate and incomplete nature. The pipeline is demonstrated on a dataset of routinely recorded data in general practice EMRs of over 260,000 patients, in which the occurrence of colorectal cancer (CRC) is predicted using various machine learning techniques (i.e., CART, LR, RF) and subsets of the data. CRC is a common type of cancer, of which early detection has proven to be important yet challenging. The results are threefold. First, the predictive models generated using our pipeline reconfirmed known predictors and identified new, medically plausible, predictors derived from the cardiovascular and metabolic disease domain, validating the pipeline's effectiveness. Second, the difference between the best model generated by the data-driven subset (AUC 0.891) and the best model generated by the current state of the art hypothesis-driven subset (AUC 0.864) is statistically significant at the 95{\\%} confidence interval level. Third, the pipeline itself is highly generic and independent of the specific disease targeted and the EMR used. In conclusion, the application of established machine learning techniques in combination with the proposed pipeline on EMRs has great potential to enhance disease prediction, and hence early detection and intervention in medical practice},\nauthor = {Kop, Reinier and Hoogendoorn, Mark and ten Teije, Annette and {B{\\"{u}}chner, Frederike L Slottje}, Pauline and Moons, Leon M.G. and Numans, Mattijs E.},\ndoi = {10.1016/j.compbiomed.2016.06.019},\njournal = {Computers in Biology and Medicine},\nkeywords = {Colorectal cancer,Data mining,Data processing,Electronic medical records,Machine learning},\npages = {30--38},\ntitle = {{Predictive modeling of colorectal cancer using a dedicated pre-processing pipeline on routine electronic medical}},\nurl = {http://www.sciencedirect.com/science/article/pii/S0010482516301573},\nvolume = {76},\nyear = {2016}\n}\n
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\n Over the past years, research utilizing routine care data extracted from Electronic Medical Records (EMRs) has increased tremendously. Yet there are no straightforward, standardized strategies for pre-processing these data. We propose a dedicated medical pre-processing pipeline aimed at taking on many problems and opportunities contained within EMR data, such as their temporal, inaccurate and incomplete nature. The pipeline is demonstrated on a dataset of routinely recorded data in general practice EMRs of over 260,000 patients, in which the occurrence of colorectal cancer (CRC) is predicted using various machine learning techniques (i.e., CART, LR, RF) and subsets of the data. CRC is a common type of cancer, of which early detection has proven to be important yet challenging. The results are threefold. First, the predictive models generated using our pipeline reconfirmed known predictors and identified new, medically plausible, predictors derived from the cardiovascular and metabolic disease domain, validating the pipeline's effectiveness. Second, the difference between the best model generated by the data-driven subset (AUC 0.891) and the best model generated by the current state of the art hypothesis-driven subset (AUC 0.864) is statistically significant at the 95% confidence interval level. Third, the pipeline itself is highly generic and independent of the specific disease targeted and the EMR used. In conclusion, the application of established machine learning techniques in combination with the proposed pipeline on EMRs has great potential to enhance disease prediction, and hence early detection and intervention in medical practice\n
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\n \n \n\n \n \n \n \n \\SWISH\\ for Prototyping Clinical Guideline Interactions Theory.\n \n\n\n \n Zamborlini, V.; Wielemaker, J.; Da Silveira, M.; Pruski, C.; ten Teije, A.; and van Harmelen, F.\n \n\n\n \n\n\n\n In Proceedings of the 9th International Conference Semantic Web Applications and Tools for Life Sciences,, 2016. \n \n\n\n\n
\n\n\n \n \n \n \"\\SWISH\\Paper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Zamborlini2016b,\nauthor = {Zamborlini, Veruska and Wielemaker, Jan and {Da Silveira}, Marcos and Pruski, C{\\{}$\\backslash$'{\\{}e{\\}}{\\}}dric and ten Teije, Annette and van Harmelen, Frank},\nbooktitle = {Proceedings of the 9th International Conference Semantic Web Applications and Tools for Life Sciences,},\ntitle = {{{\\{}SWISH{\\}} for Prototyping Clinical Guideline Interactions Theory}},\nurl = {http://ceur-ws.org/Vol-1795/paper13.pdf},\nyear = {2016}\n}\n
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\n  \n 2015\n \n \n (10)\n \n \n
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\n \n \n\n \n \n \n \n Identifying Evidence Quality for Updating Evidence-based Medical Guidelines.\n \n\n\n \n Huang, Z.; Hu, Q.; Teije, A.; and Harmelen, F. V.\n \n\n\n \n\n\n\n In Riaño, D.; Lenz, R.; Miksch, S.; Peleg, M.; Reichert, M.; and ten Teije, A. (., editor(s), Knowledge Representation for Health Care, AIME 2015 International Joint Workshop, KR4HC/ProHealth 2015, Lecture Notes AI 9485, pages 51--64, 2015. Springer\n \n\n\n\n
\n\n\n \n \n \n \"IdentifyingPaper\n  \n \n\n \n \n doi\n  \n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Huang2015,\nauthor = {Huang, Zhisheng and Hu, Qing and Teije, Annette and Harmelen, Frank Van},\nbooktitle = {Knowledge Representation for Health Care, AIME 2015 International Joint Workshop, KR4HC/ProHealth 2015, Lecture Notes AI 9485},\ndoi = {ISBN 978-3-319-26585-8},\neditor = {Ria{\\~{n}}o, D. and Lenz, R. and Miksch, S. and Peleg, M. and Reichert, M. and ten Teije, A. (Eds.)},\nfile = {:Users/annette/Dropbox/AnnetteDropBoxVU/personal/Annette-www/papers-pdf/2015KR4HC-ProHealth-Springer.pdf:pdf},\npages = {51--64},\npublisher = {Springer},\ntitle = {{Identifying Evidence Quality for Updating Evidence-based Medical Guidelines}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2015KR4HC-ProHealth-Springer.pdf},\nyear = {2015}\n}\n
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\n \n \n\n \n \n \n \n Finding Evidence for Updates in Medical Guidelines.\n \n\n\n \n Reinders, R.; TenTeije, A.; and Huang, Z.\n \n\n\n \n\n\n\n In Proceedings of the 8th International Conference on Health Informatics (HEALTHINF2015), Lisbon, Portugal, 2015. \n \n\n\n\n
\n\n\n \n \n \n \"FindingPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Reinders2015,\naddress = {Lisbon, Portugal},\nauthor = {Reinders, Roelof and TenTeije, Annette and Huang, Zhisheng},\nbooktitle = {Proceedings of the 8th International Conference on Health Informatics (HEALTHINF2015)},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Reinders, TenTeije, Huang - 2015 - Finding Evidence for Updates in Medical Guidelines.pdf:pdf},\ntitle = {{Finding Evidence for Updates in Medical Guidelines}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2015HealthInf.pdf},\nyear = {2015}\n}\n
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\n \n \n\n \n \n \n \n Inferring Recommendation Interactions in Clinical Guidelines: Case-studies on Multimorbidity.\n \n\n\n \n Zamborlini, V.; Hoekstra, R.; da Silveira, M.; Pruski, C.; ten Teije, A.; and van Harmelen, F.\n \n\n\n \n\n\n\n Semantic Web Journal, Invited submission - Accepted, Open Acess, . 2015.\n \n\n\n\n
\n\n\n \n \n \n \"InferringPaper\n  \n \n\n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@article{ZamborliniSWJ2015,\nabstract = {The formal representation of clinical knowledge is still an open research topic. Classical representation languages for clinical guidelines are used to produce diagnostic and treatment plans. However, they have important limitations, e.g. when looking for ways to re-use, combine, and reason over existing clinical knowledge. These limitations are especially problematic in the context of multimorbidity; patients that suffer from multiple diseases. To overcome these limitations, this paper proposes a model for clinical guidelines (TMR4I) that allows the re-use and combination of knowledge from multiple guidelines. Semantic Web technology is applied to implement the model, allowing us to automatically infer interactions between recommendations, such as recommending the same drug more than once. It relies on an existing Linked Data set, DrugBank, for identifying drug-drug interactions. We evaluate the model by applying it to two realistic case studies on multimorbidity that combine guidelines for two (Duodenal Ulcer and Transient Ischemic Attack) and three diseases (Osteoarthritis, Hypertension and Diabetes) and compare the results with existing methods.},\nauthor = {Zamborlini, Veruska and Hoekstra, Rinke and da Silveira, Marcos and Pruski, C{\\'{e}}dric and ten Teije, Annette and van Harmelen, Frank},\njournal = {Semantic Web Journal, Invited submission - Accepted, Open Acess},\ntitle = {{Inferring Recommendation Interactions in Clinical Guidelines: Case-studies on Multimorbidity}},\nurl = {http://www.semantic-web-journal.net/content/inferring-recommendation-interactions-clinical-guidelines-case-studies-multimorbidity-0},\nyear = {2015}\n}\n
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\n The formal representation of clinical knowledge is still an open research topic. Classical representation languages for clinical guidelines are used to produce diagnostic and treatment plans. However, they have important limitations, e.g. when looking for ways to re-use, combine, and reason over existing clinical knowledge. These limitations are especially problematic in the context of multimorbidity; patients that suffer from multiple diseases. To overcome these limitations, this paper proposes a model for clinical guidelines (TMR4I) that allows the re-use and combination of knowledge from multiple guidelines. Semantic Web technology is applied to implement the model, allowing us to automatically infer interactions between recommendations, such as recommending the same drug more than once. It relies on an existing Linked Data set, DrugBank, for identifying drug-drug interactions. We evaluate the model by applying it to two realistic case studies on multimorbidity that combine guidelines for two (Duodenal Ulcer and Transient Ischemic Attack) and three diseases (Osteoarthritis, Hypertension and Diabetes) and compare the results with existing methods.\n
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\n \n \n\n \n \n \n \n Identification of patients at risk for colorectal cancer in primary care: an explorative study with routine healthcare data.\n \n\n\n \n Koning, N. R; Moons, L. M.; Büchner, F. L; Helsper, C. W; ten Teije, A.; and Numans, M. E\n \n\n\n \n\n\n\n European journal of gastroenterology & hepatology, 12: 1443--8. 2015.\n \n\n\n\n
\n\n\n \n \n \n \"IdentificationPaper\n  \n \n\n \n \n doi\n  \n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@article{Koning2015,\nauthor = {Koning, Nynke R and Moons, Leon M.G and Büchner, Frederike L and Helsper, Charles W and ten Teije, Annette and Numans, Mattijs E},\ndoi = {10.1097/MEG.0000000000000472.},\nfile = {:Users/annette/Dropbox/AnnetteDropBoxVU/personal/Annette-www/papers-pdf/2015EJGH.pdf:pdf},\njournal = {European journal of gastroenterology {\\&} hepatology},\npages = {1443--8},\ntitle = {{Identification of patients at risk for colorectal cancer in primary care: an explorative study with routine healthcare data}},\nurl = {http://www.ncbi.nlm.nih.gov/pubmed/26398457},\nvolume = {12},\nyear = {2015}\n}\n
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\n \n \n\n \n \n \n \n Knowledge Representation for Health Care (AIME 2015 International Joint Workshop, KR4HC/ProHealth 2015).\n \n\n\n \n Riaño, D.; Lenz, R.; Miksch, S.; Peleg, M.; Reichert, M.; and ten Teije, A.\n , editor\n s.\n \n\n\n \n\n\n\n Springer, LNAI 9485 edition, 2015.\n \n\n\n\n
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@book{Riano2015,\ndoi = {10.1007/978-3-319-26585-8},\nedition = {LNAI 9485},\neditor = {Ria{\\~{n}}o, D. and Lenz, R. and Miksch, S. and Peleg, M. and Reichert, M. and ten Teije, A.},\nisbn = {978-3-319-26584-1},\npages = {145},\npublisher = {Springer},\ntitle = {{Knowledge Representation for Health Care (AIME 2015 International Joint Workshop, KR4HC/ProHealth 2015)}},\nurl = {http://www.springer.com/gp/book/9783319265841},\nyear = {2015}\n}\n
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\n \n \n\n \n \n \n \n A Compact In-Memory Dictionary for RDF data.\n \n\n\n \n Bazoobandi, H. R; De Rooij, S.; Urbani, J.; Ten Teije, A.; Van Harmelen, F.; and Bal, H.\n \n\n\n \n\n\n\n In twelfth European Semantic Web Conference, ESWC, (LNCS 9088), pages 205--220, 2015. Springer\n \n\n\n\n
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@inproceedings{Bazoobandi2015,\nabstract = {While almost all dictionary compression techniques focus on static RDF data, we present a compact in-memory RDF dictionary for dynamic and streaming data. To do so, we analysed the structure of terms in real-world datasets and observed a high degree of common prefixes. We studied the applicability of Trie data structures on RDF data to reduce the memory occupied by common prefixes and discovered that all existing Trie implementations lead to either poor performance, or an excessive memory wastage. In our approach, we address the existing limitations of Tries for RDF data, and propose a new variant of Trie which contains some optimiza-tions explicitly designed to improve the performance on RDF data. Fur-thermore, we show how we use this Trie as an in-memory dictionary by using as numerical ID a memory address instead of an integer counter. This design removes the need for an additional decoding data structure, and further reduces the occupied memory. An empirical analysis on real-world datasets shows that with a reasonable overhead our technique uses 50-59{\\%} less memory than a conventional uncompressed dictionary.},\nauthor = {Bazoobandi, Hamid R and {De Rooij}, Steven and Urbani, Jacopo and {Ten Teije}, Annette and {Van Harmelen}, Frank and Bal, Henri},\nbooktitle = {twelfth European Semantic Web Conference, ESWC, (LNCS 9088)},\npages = {205--220},\npublisher = {Springer},\ntitle = {{A Compact In-Memory Dictionary for RDF data}},\nurl = {http://www.cs.vu.nl/{~}frankh/postscript/ESWC15.pdf http://www.cs.vu.nl/{~}annette/papers-pdf/2015ESWC-RDFVault.pdf},\nyear = {2015}\n}\n
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\n While almost all dictionary compression techniques focus on static RDF data, we present a compact in-memory RDF dictionary for dynamic and streaming data. To do so, we analysed the structure of terms in real-world datasets and observed a high degree of common prefixes. We studied the applicability of Trie data structures on RDF data to reduce the memory occupied by common prefixes and discovered that all existing Trie implementations lead to either poor performance, or an excessive memory wastage. In our approach, we address the existing limitations of Tries for RDF data, and propose a new variant of Trie which contains some optimiza-tions explicitly designed to improve the performance on RDF data. Fur-thermore, we show how we use this Trie as an in-memory dictionary by using as numerical ID a memory address instead of an integer counter. This design removes the need for an additional decoding data structure, and further reduces the occupied memory. An empirical analysis on real-world datasets shows that with a reasonable overhead our technique uses 50-59% less memory than a conventional uncompressed dictionary.\n
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\n \n \n\n \n \n \n \n Enhancing Reuse of Structured Eligibility Criteria and Supporting their Relaxation.\n \n\n\n \n Milian, K.; Hoekstra, R.; Bucur, A.; Ten Teije, A.; Van Harmelen, F.; and Paulissen, J.\n \n\n\n \n\n\n\n Journal of Biomedical Informatics, 56(C): 205--219. 2015.\n \n\n\n\n
\n\n\n \n \n \n \"EnhancingPaper\n  \n \n\n \n \n doi\n  \n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@article{Milian2015,\nabstract = {Patient recruitment is one of the most important barriers to successful com-pletion of clinical trials and thus to obtaining evidence about new methods for prevention, diagnostics and treatment. The reason is that recruitment is effort consuming. It requires the identification of candidate patients for the trial (the population under study), and verifying for each patient whether the eligibility criteria are met. The work we describe in this paper aims to support the comparison of population under study in different trials, and the design of eligibility criteria for new trials. We do this by introducing structured eligibility criteria, that enhance reuse of criteria across trials. We developed a method that allows for automated structuring of criteria from text. Additionally, structured eiligibility criteria allow us to propose sugges-tions for relaxation of criteria to remove potentially unnecessarily restrictive conditions. We thereby increase the recruitment potential and generazability of a trial. Our method for automated structuring of criteria enables us to identify Preprint submitted to Journal of Biomedical Informatics October 15, 2014 related conditions and to compare their restrictiveness. The comparison is based on the general meaning of criteria, comprised of commonly occurring contextual patterns, medical concepts and constraining values. These are automatically identified using our pattern detection algorithm, state of the art ontology annotators and semantic taggers. The comparison uses prede-fined relations between the patterns, concept equivalences defined in medical ontologies, and threshold values. The result is a library of structured eligi-bility criteria which can be browsed using fine-grained queries. Furthermore, we developed visualizations for the library that enable intuitive navigation of relations between trials, criteria and concepts. These visualizations ex-pose interesting co-occurrences and correlations, potentially enhancing meta-research. The method for criteria structuring processes only certain types of crite-ria, which results in low recall of the method (18{\\%}) but a high precision for the relations we identify between the criteria (94{\\%}). Analysis of the approach from the medical perspective revealed that the approach can be beneficial for supporting trial design, though more research is needed.},\nauthor = {Milian, Krystyna and Hoekstra, Rinke and Bucur, Anca and {Ten Teije}, Annette and {Van Harmelen}, Frank and Paulissen, John},\ndoi = {10.1016/j.jbi.2015.05.005},\nfile = {:Users/annette/Dropbox/AnnetteDropBoxVU/personal/Annette-www/papers-pdf/2015IJB.pdf:pdf},\njournal = {Journal of Biomedical Informatics},\nkeywords = {data visualization,formalizing eligibility criteria,populating ontology from text,semantic annotation,supporting trial design},\nnumber = {C},\npages = {205--219},\ntitle = {{Enhancing Reuse of Structured Eligibility Criteria and Supporting their Relaxation}},\nurl = {http://www.cs.vu.nl/{~}frankh/postscript/JBI15.pdf http://www.cs.vu.nl/{~}annette/papers-pdf/2015IJB.pdf},\nvolume = {56},\nyear = {2015}\n}\n
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\n Patient recruitment is one of the most important barriers to successful com-pletion of clinical trials and thus to obtaining evidence about new methods for prevention, diagnostics and treatment. The reason is that recruitment is effort consuming. It requires the identification of candidate patients for the trial (the population under study), and verifying for each patient whether the eligibility criteria are met. The work we describe in this paper aims to support the comparison of population under study in different trials, and the design of eligibility criteria for new trials. We do this by introducing structured eligibility criteria, that enhance reuse of criteria across trials. We developed a method that allows for automated structuring of criteria from text. Additionally, structured eiligibility criteria allow us to propose sugges-tions for relaxation of criteria to remove potentially unnecessarily restrictive conditions. We thereby increase the recruitment potential and generazability of a trial. Our method for automated structuring of criteria enables us to identify Preprint submitted to Journal of Biomedical Informatics October 15, 2014 related conditions and to compare their restrictiveness. The comparison is based on the general meaning of criteria, comprised of commonly occurring contextual patterns, medical concepts and constraining values. These are automatically identified using our pattern detection algorithm, state of the art ontology annotators and semantic taggers. The comparison uses prede-fined relations between the patterns, concept equivalences defined in medical ontologies, and threshold values. The result is a library of structured eligi-bility criteria which can be browsed using fine-grained queries. Furthermore, we developed visualizations for the library that enable intuitive navigation of relations between trials, criteria and concepts. These visualizations ex-pose interesting co-occurrences and correlations, potentially enhancing meta-research. The method for criteria structuring processes only certain types of crite-ria, which results in low recall of the method (18%) but a high precision for the relations we identify between the criteria (94%). Analysis of the approach from the medical perspective revealed that the approach can be beneficial for supporting trial design, though more research is needed.\n
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\n \n \n\n \n \n \n \n On the Advantage of Using Dedicated Data Mining Techniques to Predict Colorectal Cancer.\n \n\n\n \n Kop, R.; Hoogendoorn, M.; Moons, L. M G; Numans, M. E; and ten Teije, A.\n \n\n\n \n\n\n\n In Artificial Intelligence in Medicine, 15th Conference on Artificial Intelligence in Medicine, AIME 2015, Pavia, Italy, June 17-20, 2015, Proceedings AIME, pages 133--142, 2015. Springer\n \n\n\n\n
\n\n\n \n \n \n \"OnPaper\n  \n \n\n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
\n
@inproceedings{Kop,\nabstract = {Electronic Medical Records (EMRs) provide a wealth of data that can be used to generate predictive models for diseases. Quite some studies have been performed that use EMRs to generate such models for specific diseases, but most of them are based on more traditional tech- niques used in medical domain, such as logistic regression. This paper studies the benefit of using advanced data mining techniques for Col- orectal Cancer (CRC). CRC is the second most common cause of death in the EU and is known to be a disease with very a-specific predictors, making it di},\nauthor = {Kop, Reinier and Hoogendoorn, Mark and Moons, Leon M G and Numans, Matthijs E and ten Teije, Annette},\nbooktitle = {Artificial Intelligence in Medicine, 15th Conference on Artificial Intelligence in Medicine, AIME 2015, Pavia, Italy, June 17-20, 2015, Proceedings AIME},\nfile = {:Users/annette/Dropbox/AnnetteDropBoxVU/personal/Annette-www/papers-pdf/2015AIME-Kop.pdf:pdf},\nkeywords = {colorectal cancer,data mining,machine learning},\npages = {133--142},\npublisher = {Springer},\ntitle = {{On the Advantage of Using Dedicated Data Mining Techniques to Predict Colorectal Cancer}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2015AIMEKop.pdf},\nyear = {2015}\n}\n
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\n Electronic Medical Records (EMRs) provide a wealth of data that can be used to generate predictive models for diseases. Quite some studies have been performed that use EMRs to generate such models for specific diseases, but most of them are based on more traditional tech- niques used in medical domain, such as logistic regression. This paper studies the benefit of using advanced data mining techniques for Col- orectal Cancer (CRC). CRC is the second most common cause of death in the EU and is known to be a disease with very a-specific predictors, making it di\n
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\n \n \n\n \n \n \n \n Analyzing Recommendations Interactions in Clinical Guidelines Impact of action type hierarchies and causation beliefs.\n \n\n\n \n Zamborlini, V.; Da Silveira, M.; Pruski, C.; Ten Teije, A.; and Van Harmelen, F.\n \n\n\n \n\n\n\n In 15th Conference on Artificial Intelligence in Medicine \\AIME 2015\\, pages 317--326, 2015. \n \n\n\n\n
\n\n\n \n \n \n \"AnalyzingPaper\n  \n \n\n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Zamborlini2015,\nabstract = {Accounting for patients with multiple health conditions is a complex task that requires analysing potential interactions among recom-mendations meant to address each condition. Although some approaches have been proposed to address this issue, important features still require more investigation, such as (re)usability and scalability. To this end, this paper presents an approach that relies on reusable rules for detecting interactions among recommendations coming from various guidelines. It extends previously proposed models by introducing the notions of action type hierarchy and causation beliefs, and provides a systematic analy-sis of relevant interactions in the context of multimorbidity. Finally, the approach is assessed based on a case-study taken from the literature to highlight the added value of the approach.},\nauthor = {Zamborlini, Veruska and {Da Silveira}, Marcos and Pruski, Cedric and {Ten Teije}, Annette and {Van Harmelen}, Frank},\nbooktitle = {15th Conference on Artificial Intelligence in Medicine {\\{}AIME 2015{\\}}},\nkeywords = {Clinical knowledge representation,Combining medical guide-lines,Multimorbidity},\npages = {317--326},\ntitle = {{Analyzing Recommendations Interactions in Clinical Guidelines Impact of action type hierarchies and causation beliefs}},\nurl = {http://www.cs.vu.nl/{~}frankh/postscript/AIME15-GuidelineInteraction.pdf http://www.cs.vu.nl/{~}annette/papers-pdf/2015AIME-Zamborlini.pdf},\nyear = {2015}\n}\n
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\n Accounting for patients with multiple health conditions is a complex task that requires analysing potential interactions among recom-mendations meant to address each condition. Although some approaches have been proposed to address this issue, important features still require more investigation, such as (re)usability and scalability. To this end, this paper presents an approach that relies on reusable rules for detecting interactions among recommendations coming from various guidelines. It extends previously proposed models by introducing the notions of action type hierarchy and causation beliefs, and provides a systematic analy-sis of relevant interactions in the context of multimorbidity. Finally, the approach is assessed based on a case-study taken from the literature to highlight the added value of the approach.\n
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\n \n \n\n \n \n \n \n Detecting New Evidence for Evidence-based Guidelines Using a Semantic Distance Method.\n \n\n\n \n Hu, Q.; Huang, Z.; Ten Teije, A.; and Van Harmelen, F.\n \n\n\n \n\n\n\n In Artificial Intelligence in Medicine, 15th Conference on Artificial Intelligence in Medicine, AIME 2015, Pavia, Italy, June 17-20, 2015, Proceedings AIME, pages 307--316, 2015. Springer\n \n\n\n\n
\n\n\n \n \n \n \"DetectingPaper\n  \n \n\n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
\n
@inproceedings{Hu2015,\nabstract = {To ensure timely use of new results from medical research in daily medical practice, evidence-based medical guidelines must be up-dated using the latest medical articles as evidences. Finding such new relevant medical evidence manually is time consuming and labor inten-sive. Traditional information retrieval methods can improve the efficiency of finding evidence from the medical literature, but they usually require a large training corpus for determining relevance. This means that both the manual approach and traditional IR approaches are not suitable for automatically finding new medical evidence in realtime. This paper pro-pose the use of a semantic distance measure to automatically find rele-vant new evidence to support guideline updates. The advantage of using our semantic distance measure is that this relevance measure can be easily obtained from a search engine (e.g., PubMed), rather then gather-ing a large corpus for analysis. We have conducted several experiments that use our semantic distance measure to find new relevant evidence for guideline updates. We selected two versions of the Dutch Breast Cancer Guidelines (2004 and 2012), and we checked if the new evidence items in the 2012 version could be found by using our method. The experiment shows that our method can not only find at least some evidence for 10 out of the 16 guideline statements in our experiment (i.e. a reasonable recall), but it also returns reasonably small numbers of evidence candi-dates (i.e. a good precision) with an acceptable real-time performance (an average of approximately 10 minutes for each guideline statement).},\nauthor = {Hu, Qing and Huang, Zhisheng and {Ten Teije}, Annette and {Van Harmelen}, Frank},\nbooktitle = {Artificial Intelligence in Medicine, 15th Conference on Artificial Intelligence in Medicine, AIME 2015, Pavia, Italy, June 17-20, 2015, Proceedings AIME},\nfile = {:Users/annette/Dropbox/AnnetteDropBoxVU/research/conferences/2015AIME/papers/final/2015AIMEguidelineSDQingHuFinal.pdf:pdf},\npages = {307--316},\npublisher = {Springer},\ntitle = {{Detecting New Evidence for Evidence-based Guidelines Using a Semantic Distance Method}},\nurl = {http://www.cs.vu.nl/{~}frankh/postscript/AIME15-GuidelineUpdate.pdf http://www.cs.vu.nl/{~}annette/papers-pdf/2015AIMEguidelineSDQingHu.pdf},\nyear = {2015}\n}\n
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\n\n\n
\n To ensure timely use of new results from medical research in daily medical practice, evidence-based medical guidelines must be up-dated using the latest medical articles as evidences. Finding such new relevant medical evidence manually is time consuming and labor inten-sive. Traditional information retrieval methods can improve the efficiency of finding evidence from the medical literature, but they usually require a large training corpus for determining relevance. This means that both the manual approach and traditional IR approaches are not suitable for automatically finding new medical evidence in realtime. This paper pro-pose the use of a semantic distance measure to automatically find rele-vant new evidence to support guideline updates. The advantage of using our semantic distance measure is that this relevance measure can be easily obtained from a search engine (e.g., PubMed), rather then gather-ing a large corpus for analysis. We have conducted several experiments that use our semantic distance measure to find new relevant evidence for guideline updates. We selected two versions of the Dutch Breast Cancer Guidelines (2004 and 2012), and we checked if the new evidence items in the 2012 version could be found by using our method. The experiment shows that our method can not only find at least some evidence for 10 out of the 16 guideline statements in our experiment (i.e. a reasonable recall), but it also returns reasonably small numbers of evidence candi-dates (i.e. a good precision) with an acceptable real-time performance (an average of approximately 10 minutes for each guideline statement).\n
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\n  \n 2014\n \n \n (8)\n \n \n
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\n \n \n\n \n \n \n \n Semantic Representation of Evidence-based Clinical Guidelines.\n \n\n\n \n Huang, Z.; ten Teije, A.; van Harmelen, F.; and Ait-Mokhtar, S.\n \n\n\n \n\n\n\n In 6th International Workshop on Knowledge Representation for Health Care (KR4HC2014), LNCS Volume 8903. 2014.\n \n\n\n\n
\n\n\n \n \n \n \"SemanticPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n  \n\n \n buy\n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@incollection{Huang2014,\nauthor = {Huang, Zhisheng and ten Teije, Annete and van Harmelen, Frank and Ait-Mokhtar, Salah},\nbooktitle = {6th International Workshop on Knowledge Representation for Health Care (KR4HC2014), LNCS Volume 8903},\ntitle = {{Semantic Representation of Evidence-based Clinical Guidelines}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2014KR4HC-Huang.pdf},\nyear = {2014}\n}\n
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\n \n \n\n \n \n \n \n A Conceptual Model for Detecting Interactions among Medical Recommendations in Clinical Guidelines.\n \n\n\n \n Zamborlini, V.; Da Silveira, M.; Pruski, C.; Hoekstra, R.; ten Teije, A.; and van Harmelen, F.\n \n\n\n \n\n\n\n In Schlobach, S.; and Janowicz, K., editor(s), Proceedings of the 19th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2014), 2014. Springer\n \n\n\n\n
\n\n\n \n \n \n \"APaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Zamborlini2013,\nauthor = {Zamborlini, Veruska and {Da Silveira}, Marcos and Pruski, C{\\'{e}}dric and Hoekstra, Rinke and ten Teije, Annette and van Harmelen, Frank},\nbooktitle = {Proceedings of the 19th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2014)},\neditor = {Schlobach, Stefan and Janowicz, Krzysztof},\npublisher = {Springer},\ntitle = {{A Conceptual Model for Detecting Interactions among Medical Recommendations in Clinical Guidelines}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2014EKAW.pdf},\nyear = {2014}\n}\n
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\n \n \n\n \n \n \n \n Influence of data quality on computed Dutch hospital quality indicators: a case study in colorectal cancer surgery.\n \n\n\n \n Dentler, K.; Cornet, R.; ten Teije, A.; Tanis, P.; Klinkenbijl, J.; Tytgat, K.; and de Keizer, N.\n \n\n\n \n\n\n\n BMC medical informatics and decision making, 14: 32. jan 2014.\n \n\n\n\n
\n\n\n \n \n \n \"InfluencePaper\n  \n \n\n \n \n doi\n  \n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@article{Dentler2014a,\nabstract = {BACKGROUND: Our study aims to assess the influence of data quality on computed Dutch hospital quality indicators, and whether colorectal cancer surgery indicators can be computed reliably based on routinely recorded data from an electronic medical record (EMR). METHODS: Cross-sectional study in a department of gastrointestinal oncology in a university hospital, in which a set of 10 indicators is computed (1) based on data abstracted manually for the national quality register Dutch Surgical Colorectal Audit (DSCA) as reference standard and (2) based on routinely collected data from an EMR. All 75 patients for whom data has been submitted to the DSCA for the reporting year 2011 and all 79 patients who underwent a resection of a primary colorectal carcinoma in 2011 according to structured data in the EMR were included. Comparison of results, investigating the causes for any differences based on data quality analysis. Main outcome measures are the computability of quality indicators, absolute percentages of indicator results, data quality in terms of availability in a structured format, completeness and correctness. RESULTS: All indicators were fully computable based on the DSCA dataset, but only three based on EMR data, two of which were percentages. For both percentages, the difference in proportions computed based on the two datasets was significant.All required data items were available in a structured format in the DSCA dataset. Their average completeness was 86{\\%}, while the average completeness of these items in the EMR was 50{\\%}. Their average correctness was 87{\\%}. CONCLUSIONS: Our study showed that data quality can significantly influence indicator results, and that our EMR data was not suitable to reliably compute quality indicators. EMRs should be designed in a way so that the data required for audits can be entered directly in a structured and coded format.},\nauthor = {Dentler, Kathrin and Cornet, Ronald and ten Teije, Annette and Tanis, Pieter and Klinkenbijl, Jean and Tytgat, Kristien and de Keizer, Nicolette},\ndoi = {10.1186/1472-6947-14-32},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Dentler et al. - 2014 - Influence of data quality on computed Dutch hospital quality indicators a case study in colorectal cancer surger.pdf:pdf},\nissn = {1472-6947},\njournal = {BMC medical informatics and decision making},\nkeywords = {Carcinoma,Carcinoma: epidemiology,Carcinoma: surgery,Clinical Audit,Clinical Audit: standards,Colorectal Neoplasms,Colorectal Neoplasms: epidemiology,Colorectal Neoplasms: surgery,Cross-Sectional Studies,Electronic Health Records,Electronic Health Records: standards,Health Care,Health Care: standards,Hospital Departments,Hospital Departments: standards,Humans,Netherlands,Quality Indicators,Registries,Research Design,Research Design: standards},\nmonth = {jan},\npages = {32},\npmid = {24721489},\ntitle = {{Influence of data quality on computed Dutch hospital quality indicators: a case study in colorectal cancer surgery.}},\nurl = {/pmc/articles/PMC4004502/?report=abstract http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4004502{\\&}tool=pmcentrez{\\&}rendertype=abstract http://www.cs.vu.nl/{~}annette/papers-pdf/2014BMC1472-6947-14-32.pdf},\nvolume = {14},\nyear = {2014}\n}\n
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\n BACKGROUND: Our study aims to assess the influence of data quality on computed Dutch hospital quality indicators, and whether colorectal cancer surgery indicators can be computed reliably based on routinely recorded data from an electronic medical record (EMR). METHODS: Cross-sectional study in a department of gastrointestinal oncology in a university hospital, in which a set of 10 indicators is computed (1) based on data abstracted manually for the national quality register Dutch Surgical Colorectal Audit (DSCA) as reference standard and (2) based on routinely collected data from an EMR. All 75 patients for whom data has been submitted to the DSCA for the reporting year 2011 and all 79 patients who underwent a resection of a primary colorectal carcinoma in 2011 according to structured data in the EMR were included. Comparison of results, investigating the causes for any differences based on data quality analysis. Main outcome measures are the computability of quality indicators, absolute percentages of indicator results, data quality in terms of availability in a structured format, completeness and correctness. RESULTS: All indicators were fully computable based on the DSCA dataset, but only three based on EMR data, two of which were percentages. For both percentages, the difference in proportions computed based on the two datasets was significant.All required data items were available in a structured format in the DSCA dataset. Their average completeness was 86%, while the average completeness of these items in the EMR was 50%. Their average correctness was 87%. CONCLUSIONS: Our study showed that data quality can significantly influence indicator results, and that our EMR data was not suitable to reliably compute quality indicators. EMRs should be designed in a way so that the data required for audits can be entered directly in a structured and coded format.\n
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\n \n \n\n \n \n \n \n Evidence-based Clinical Guideliens in SemanticCT.\n \n\n\n \n Hu, Q.; Huang, Z.; van Harmelen, F.; ten Teije, A.; and Gu, J.\n \n\n\n \n\n\n\n In 8th China Semantic Web Symposium & 3rd Web Science Conference (CSWS2014), 2014. \n \n\n\n\n
\n\n\n \n \n \n \"Evidence-basedPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Hu2014,\nauthor = {Hu, Quin and Huang, Zhisheng and van Harmelen, Frank and ten Teije, Annette and Gu, Jinguang},\nbooktitle = {8th China Semantic Web Symposium {\\&} 3rd Web Science Conference (CSWS2014)},\ntitle = {{Evidence-based Clinical Guideliens in SemanticCT}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2014CSWS.pdf},\nyear = {2014}\n}\n
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\n \n \n\n \n \n \n \n Towards a Conceptual Model for Enhancing Reasoning about Clinical Guidelines: A case-study on Comorbidity.\n \n\n\n \n Zamborlini, V.; da Silveira, M.; Pruski, C.; ten Teije, A.; and van Harmelen, F.\n \n\n\n \n\n\n\n In Proceedings of 6th International Workshop Knowledge Representation for Health-Care (KR4HC). Lecture Notes in Computer Science, vol. 8903 LNCS., of Lecture Notes in Computer Science, Vienna, Austria, 2014. Springer Berlin Heidelberg\n \n\n\n\n
\n\n\n \n \n \n \"TowardsPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{ZamborliniKR4HC2014,\naddress = {Vienna, Austria},\nauthor = {Zamborlini, Veruska and da Silveira, Marcos and Pruski, C{\\'{e}}dric and ten Teije, Annette and van Harmelen, Frank},\nbooktitle = {Proceedings of 6th International Workshop Knowledge Representation for Health-Care (KR4HC). Lecture Notes in Computer Science, vol. 8903 LNCS.},\npublisher = {Springer Berlin Heidelberg},\nseries = {Lecture Notes in Computer Science},\ntitle = {{Towards a Conceptual Model for Enhancing Reasoning about Clinical Guidelines: A case-study on Comorbidity}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2014KR4HC-Zamborlini.pdf},\nyear = {2014}\n}\n
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\n \n \n\n \n \n \n \n Knowledge Representation for Health Care (6th International Workshop KR4HC 2014).\n \n\n\n \n Miksch, S.; Riaño, D.; and Ten Teije, A.\n \n\n\n \n\n\n\n Springer Berlin Heidelberg, LNAI 8903 edition, 2014.\n \n\n\n\n
\n\n\n \n \n \n \"KnowledgePaper\n  \n \n\n \n\n bibtex \n \n \n \n\n  \n\n \n buy\n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@book{Miksch2014,\nauthor = {Miksch, Silvia and Ria{\\~{n}}o, David and {Ten Teije}, Annette},\nedition = {LNAI 8903},\neditor = {Miksch, Silvia and Ria{\\~{n}}o, David and {Ten Teije}, Annette},\nisbn = {ISBN 978-3-319-13280-8},\npages = {175},\npublisher = {Springer Berlin Heidelberg},\ntitle = {{Knowledge Representation for Health Care (6th International Workshop KR4HC 2014)}},\nurl = {http://www.springer.com/computer/ai/book/978-3-319-13280-8},\nyear = {2014}\n}\n
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\n \n \n\n \n \n \n \n Feasibility Estimation for Clinical Trials.\n \n\n\n \n Huang, Z.; van Harmelen, F.; ten Teije, A.; and Dekker, A.\n \n\n\n \n\n\n\n In Proceedings of the 7th International Conference on Health Informatics (HEALTHINF2014), pages 68--77, 2014. \n \n\n\n\n
\n\n\n \n \n \n \"FeasibilityPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Huang2014a,\nauthor = {Huang, Zhisheng and van Harmelen, Frank and ten Teije, Annette and Dekker, Andre},\nbooktitle = {Proceedings of the 7th International Conference on Health Informatics (HEALTHINF2014)},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Huang et al. - 2014 - Feasibility Estimation for Clinical Trials.pdf:pdf},\npages = {68--77},\ntitle = {{Feasibility Estimation for Clinical Trials}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2014HealthInf.pdf},\nyear = {2014}\n}\n
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\n \n \n\n \n \n \n \n Formalization and computation of quality measures based on electronic medical records.\n \n\n\n \n Dentler, K; Numans, M E; ten Teije, A; Cornet, R; and de Keizer, N F\n \n\n\n \n\n\n\n Journal of the American Medical Informatics Association : JAMIA, 21: 285--291. 2014.\n \n\n\n\n
\n\n\n \n \n \n \"FormalizationPaper\n  \n \n\n \n \n doi\n  \n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@article{Dentler2014,\nabstract = {OBJECTIVE: Ambiguous definitions of quality measures in natural language impede their automated computability and also the reproducibility, validity, timeliness, traceability, comparability, and interpretability of computed results. Therefore, quality measures should be formalized before their release. We have previously developed and successfully applied a method for clinical indicator formalization (CLIF). The objective of our present study is to test whether CLIF is generalizable--that is, applicable to a large set of heterogeneous measures of different types and from various domains. MATERIALS AND METHODS: We formalized the entire set of 159 Dutch quality measures for general practice, which contains structure, process, and outcome measures and covers seven domains. We relied on a web-based tool to facilitate the application of our method. Subsequently, we computed the measures on the basis of a large database of real patient data. RESULTS: Our CLIF method enabled us to fully formalize 100{\\%} of the measures. Owing to missing functionality, the accompanying tool could support full formalization of only 86{\\%} of the quality measures into Structured Query Language (SQL) queries. The remaining 14{\\%} of the measures required manual application of our CLIF method by directly translating the respective criteria into SQL. The results obtained by computing the measures show a strong correlation with results computed independently by two other parties. CONCLUSIONS: The CLIF method covers all quality measures after having been extended by an additional step. Our web tool requires further refinement for CLIF to be applied completely automatically. We therefore conclude that CLIF is sufficiently generalizable to be able to formalize the entire set of Dutch quality measures for general practice.},\nauthor = {Dentler, K and Numans, M E and ten Teije, A and Cornet, R and de Keizer, N F},\ndoi = {10.1136/amiajnl-2013-001921 [doi]},\nissn = {1527-974X; 1067-5027},\njournal = {Journal of the American Medical Informatics Association : JAMIA},\nkeywords = {EMR-driven Phenotyping,Electronic Medical Record,Identification of Patient Cohorts,Quality Indicators,Quality Measures,Secondary Use of Patient Data},\npages = {285--291},\ntitle = {{Formalization and computation of quality measures based on electronic medical records}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2014JAMIADentler.pdf},\nvolume = {21},\nyear = {2014}\n}\n
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\n OBJECTIVE: Ambiguous definitions of quality measures in natural language impede their automated computability and also the reproducibility, validity, timeliness, traceability, comparability, and interpretability of computed results. Therefore, quality measures should be formalized before their release. We have previously developed and successfully applied a method for clinical indicator formalization (CLIF). The objective of our present study is to test whether CLIF is generalizable--that is, applicable to a large set of heterogeneous measures of different types and from various domains. MATERIALS AND METHODS: We formalized the entire set of 159 Dutch quality measures for general practice, which contains structure, process, and outcome measures and covers seven domains. We relied on a web-based tool to facilitate the application of our method. Subsequently, we computed the measures on the basis of a large database of real patient data. RESULTS: Our CLIF method enabled us to fully formalize 100% of the measures. Owing to missing functionality, the accompanying tool could support full formalization of only 86% of the quality measures into Structured Query Language (SQL) queries. The remaining 14% of the measures required manual application of our CLIF method by directly translating the respective criteria into SQL. The results obtained by computing the measures show a strong correlation with results computed independently by two other parties. CONCLUSIONS: The CLIF method covers all quality measures after having been extended by an additional step. Our web tool requires further refinement for CLIF to be applied completely automatically. We therefore conclude that CLIF is sufficiently generalizable to be able to formalize the entire set of Dutch quality measures for general practice.\n
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\n  \n 2013\n \n \n (10)\n \n \n
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\n \n \n\n \n \n \n \n Process Support and Knowledge Representation in Health Care (BPM 2012 Joint Workshop, ProHealth 2012/KR4HC 2012), Lecture Notes in Computer Science, Vol. 7738.\n \n\n\n \n Lenz, R.; Miksch, S.; Peleg, M.; Reichert, M.; Riaño, D.; and ten Teije, A.\n , editor\n s.\n \n\n\n \n\n\n\n Springer, 2013.\n \n\n\n\n
\n\n\n \n \n \n \"ProcessPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n  \n\n \n buy\n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@book{Lenz2013,\neditor = {Lenz, Richard and Miksch, Silvia and Peleg, Mor and Reichert, Manfred and Ria{\\~{n}}o, David and ten Teije, Annette},\nisbn = {ISBN 978-3-642-36438-9},\npublisher = {Springer},\ntitle = {{Process Support and Knowledge Representation in Health Care (BPM 2012 Joint Workshop, ProHealth 2012/KR4HC 2012), Lecture Notes in Computer Science, Vol. 7738}},\nurl = {http://www.springer.com/computer/ai/book/978-3-642-36437-2},\nyear = {2013}\n}\n
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\n \n \n\n \n \n \n \n Rule-based formalization of eligibility criteria for clinical trials.\n \n\n\n \n Huang, Z.; ten Teije, A.; and van Harmelen, F.\n \n\n\n \n\n\n\n In 14th Conference on Artificial Intelligence in Medicine (AIME 2013), pages 38----47, 2013. Springer\n \n\n\n\n
\n\n\n \n \n \n \"Rule-basedPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n  \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Huang2013a,\nauthor = {Huang, Zhisheng and ten Teije, Annette and van Harmelen, Frank},\nbooktitle = {14th Conference on Artificial Intelligence in Medicine (AIME 2013)},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Huang, ten Teije, van Harmelen - 2013 - Rule-based formalization of eligibility criteria for clinical trials.pdf:pdf},\npages = {38----47},\npublisher = {Springer},\ntitle = {{Rule-based formalization of eligibility criteria for clinical trials}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2013AIME-Huang.pdf},\nyear = {2013}\n}\n
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\n \n \n\n \n \n \n \n Automated generation of patient-tailored electronic care pathways by translating computer-interpretable guidelines into hierarchical task networks.\n \n\n\n \n González-Ferrer, A.; ten Teije, A.; Fdez-Olivares, J.; and Milian, K.\n \n\n\n \n\n\n\n Artificial Intelligence in Medicine, 57: 91--109. 2013.\n \n\n\n\n
\n\n\n \n \n \n \"AutomatedPaper\n  \n \n\n \n \n doi\n  \n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n \n\n\n
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@article{Gonzalez-Ferrer2013,\nabstract = {Objective: This paper describes a methodology which enables computer-aided support for the planning, visualization and execution of personalized patient treatments in a specific healthcare process, taking into account complex temporal constraints and the allocation of institutional resources. To this end, a translation from a time-annotated computer-interpretable guideline (CIG) model of a clinical protocol into a temporal hierarchical task network (HTN) planning domain is presented. Materials and methods: The proposed method uses a knowledge-driven reasoning process to translate knowledge previously described in a CIG into a corresponding HTN Planning and Scheduling domain, taking advantage of HTNs known ability to (i) dynamically cope with temporal and resource constraints, and (ii) automatically generate customized plans. The proposed method, focusing on the representation of temporal knowledge and based on the identification of workflow and temporal patterns in a CIG, makes it possible to automatically generate time-annotated and resource-based care pathways tailored to the needs of any possible patient profile. Results: The proposed translation is illustrated through a case study based on a 70 pages long clinical protocol to manage Hodgkin's disease, developed by the Spanish Society of Pediatric Oncology. We show that an HTN planning domain can be generated from the corresponding specification of the protocol in the Asbru language, providing a running example of this translation. Furthermore, the correctness of the translation is checked and also the management of ten different types of temporal patterns represented in the protocol. By interpreting the automatically generated domain with a state-of-art HTN planner, a time-annotated care pathway is automatically obtained, customized for the patient's and institutional needs. The generated care pathway can then be used by clinicians to plan and manage the patients long-term care. Conclusion: The described methodology makes it possible to automatically generate patient-tailored care pathways, leveraging an incremental knowledge-driven engineering process that starts from the expert knowledge of medical professionals. The presented approach makes the most of the strengths inherent in both CIG languages and HTN planning and scheduling techniques: for the former, knowledge acquisition and representation of the original clinical protocol, and for the latter, knowledge reasoning capabilities and an ability to deal with complex temporal and resource constraints. Moreover, the proposed approach provides immediate access to technologies such as business process management (BPM) tools, which are increasingly being used to support healthcare processes. {\\textcopyright} 2012 Elsevier B.V.},\nauthor = {Gonz{\\'{a}}lez-Ferrer, Arturo and ten Teije, Annette and Fdez-Olivares, Juan and Milian, Krystyna},\ndoi = {10.1016/j.artmed.2012.08.008},\nisbn = {1873-2860},\nissn = {09333657},\njournal = {Artificial Intelligence in Medicine},\nkeywords = {Clinical decision support systems,Clinical pathways,Hodgkin disease,Patient care planning,Pediatric oncology,Planning and scheduling,Practice guideline},\npages = {91--109},\npmid = {23177024},\ntitle = {{Automated generation of patient-tailored electronic care pathways by translating computer-interpretable guidelines into hierarchical task networks}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2012AIIM.pdf},\nvolume = {57},\nyear = {2013}\n}\n
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\n Objective: This paper describes a methodology which enables computer-aided support for the planning, visualization and execution of personalized patient treatments in a specific healthcare process, taking into account complex temporal constraints and the allocation of institutional resources. To this end, a translation from a time-annotated computer-interpretable guideline (CIG) model of a clinical protocol into a temporal hierarchical task network (HTN) planning domain is presented. Materials and methods: The proposed method uses a knowledge-driven reasoning process to translate knowledge previously described in a CIG into a corresponding HTN Planning and Scheduling domain, taking advantage of HTNs known ability to (i) dynamically cope with temporal and resource constraints, and (ii) automatically generate customized plans. The proposed method, focusing on the representation of temporal knowledge and based on the identification of workflow and temporal patterns in a CIG, makes it possible to automatically generate time-annotated and resource-based care pathways tailored to the needs of any possible patient profile. Results: The proposed translation is illustrated through a case study based on a 70 pages long clinical protocol to manage Hodgkin's disease, developed by the Spanish Society of Pediatric Oncology. We show that an HTN planning domain can be generated from the corresponding specification of the protocol in the Asbru language, providing a running example of this translation. Furthermore, the correctness of the translation is checked and also the management of ten different types of temporal patterns represented in the protocol. By interpreting the automatically generated domain with a state-of-art HTN planner, a time-annotated care pathway is automatically obtained, customized for the patient's and institutional needs. The generated care pathway can then be used by clinicians to plan and manage the patients long-term care. Conclusion: The described methodology makes it possible to automatically generate patient-tailored care pathways, leveraging an incremental knowledge-driven engineering process that starts from the expert knowledge of medical professionals. The presented approach makes the most of the strengths inherent in both CIG languages and HTN planning and scheduling techniques: for the former, knowledge acquisition and representation of the original clinical protocol, and for the latter, knowledge reasoning capabilities and an ability to deal with complex temporal and resource constraints. Moreover, the proposed approach provides immediate access to technologies such as business process management (BPM) tools, which are increasingly being used to support healthcare processes. \\textcopyright 2012 Elsevier B.V.\n
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\n \n \n\n \n \n \n \n Process Support and Knowledge Representation in Health Care (KR4HC2013/ProHealth2013), LNCS volume 8268.\n \n\n\n \n Riaño, D.; Lenz, R.; Miksch, S.; Peleg, M.; Reichert, M.; and ten Teije, A.\n , editor\n s.\n \n\n\n \n\n\n\n Springer, 2013.\n \n\n\n\n
\n\n\n \n \n \n \"ProcessPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n  \n\n \n buy\n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@book{Riano2013,\neditor = {Ria{\\~{n}}o, David and Lenz, Richard and Miksch, Silvia and Peleg, Mor and Reichert, Manfred and ten Teije, Annette},\npublisher = {Springer},\ntitle = {{Process Support and Knowledge Representation in Health Care (KR4HC2013/ProHealth2013), LNCS volume 8268}},\nurl = {http://www.springer.com/computer/ai/book/978-3-319-03915-2},\nyear = {2013}\n}\n
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\n \n \n\n \n \n \n \n SemanticCT: A Semantically-Enabled System for Clinical Trials.\n \n\n\n \n Huang, Z.; ten Teije, A.; and van Harmelen, F.\n \n\n\n \n\n\n\n In Process Support and Knowledge Representation in Health Care, 2013. Springer\n \n\n\n\n
\n\n\n \n \n \n \"SemanticCT:Paper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n  \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Huang2013,\nauthor = {Huang, Zhishegn and ten Teije, Annette and van Harmelen, Frank},\nbooktitle = {Process Support and Knowledge Representation in Health Care},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Huang, ten Teije, van Harmelen - 2013 - SemanticCT A Semantically-Enabled System for Clinical Trials.pdf:pdf},\npublisher = {Springer},\ntitle = {{SemanticCT: A Semantically-Enabled System for Clinical Trials}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2013KR4HCsemanticct.pdf},\nyear = {2013}\n}\n
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\n \n \n\n \n \n \n \n Semantic Integration of Patient Data and Quality Indicators Based on openEHR Archetypes.\n \n\n\n \n Dentler, K.; Teije, A.; Cornet, R.; and Keizer, N. D.\n \n\n\n \n\n\n\n In Process Support and Knowledge Representation in Health Care, pages 85--97. 2013.\n \n\n\n\n
\n\n\n \n \n \n \"SemanticPaper\n  \n \n\n \n \n doi\n  \n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n  \n\n \n buy\n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@incollection{Dentler2013,\nabstract = {Electronic Health Records (EHRs) contain a wealth of information, but accessing and (re)using it is often difficult. Archetypes have been shown to facilitate the (re)use of EHR data, and may be useful with regard to clinical qual- ity indicators. These indicators are often released centrally, but computed locally in several hospitals. They are typically expressed in natural language, which due to its inherent ambiguity does not guarantee comparable results. Thus, their information requirements should be formalised and expressed via standard terminologies such as SNOMEDCT to represent concepts, and information models such as archetypes to represent their agreed-upon structure, and the relations between the concepts. The two-level methodology of the archetype paradigm allows domain experts to intuitively define indicators at the knowledge level, and the resulting queries are computable across institutions that employ the required archetypes. We tested whether openEHR archetypes can represent both elements of patient data required by indicators and EHR data for automated indicator computation. The relevant elements of the indicators and our hospital's database schema were mapped to (elements of) publicly available archetypes. The coverage of the public repository was high, and editing an archetype to fit our requirementswas straight- forward. Based on thismapping, a set of three indicators fromthe domain of gas- trointestinal cancer surgery was formalised into archetyped SPARQL queries and run against archetyped patient data inOWL fromour hospital's datawarehouse to compute the indicators. The computed indicator results were comparable to cen- trally computed and publicly reported results, with differences likely to be due to differing indicator definitions and interpretations, insufficient data quality and insufficient and imprecise encoding. This paper shows that openEHR archetypes facilitate the semantic integration of quality indicators and routine patient data to automatically compute indicators.},\nauthor = {Dentler, Kathrin and Teije, Annette and Cornet, Ronald and Keizer, Nicolette De},\nbooktitle = {Process Support and Knowledge Representation in Health Care},\ndoi = {10.1007/978-3-642-36438-9_6},\nisbn = {978-3-642-36437-2},\nissn = {03029743},\nkeywords = {EHRs,OWL,Qual- ity Indicators,SPARQL,Secondary Use of Clinical Data,Semantic Integration,openEHR Archetypes},\npages = {85--97},\ntitle = {{Semantic Integration of Patient Data and Quality Indicators Based on openEHR Archetypes}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2013KR4HC-Dentler.pdf},\nyear = {2013}\n}\n
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\n Electronic Health Records (EHRs) contain a wealth of information, but accessing and (re)using it is often difficult. Archetypes have been shown to facilitate the (re)use of EHR data, and may be useful with regard to clinical qual- ity indicators. These indicators are often released centrally, but computed locally in several hospitals. They are typically expressed in natural language, which due to its inherent ambiguity does not guarantee comparable results. Thus, their information requirements should be formalised and expressed via standard terminologies such as SNOMEDCT to represent concepts, and information models such as archetypes to represent their agreed-upon structure, and the relations between the concepts. The two-level methodology of the archetype paradigm allows domain experts to intuitively define indicators at the knowledge level, and the resulting queries are computable across institutions that employ the required archetypes. We tested whether openEHR archetypes can represent both elements of patient data required by indicators and EHR data for automated indicator computation. The relevant elements of the indicators and our hospital's database schema were mapped to (elements of) publicly available archetypes. The coverage of the public repository was high, and editing an archetype to fit our requirementswas straight- forward. Based on thismapping, a set of three indicators fromthe domain of gas- trointestinal cancer surgery was formalised into archetyped SPARQL queries and run against archetyped patient data inOWL fromour hospital's datawarehouse to compute the indicators. The computed indicator results were comparable to cen- trally computed and publicly reported results, with differences likely to be due to differing indicator definitions and interpretations, insufficient data quality and insufficient and imprecise encoding. This paper shows that openEHR archetypes facilitate the semantic integration of quality indicators and routine patient data to automatically compute indicators.\n
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\n \n \n\n \n \n \n \n Barriers to the reuse of routinely recorded clinical data: A field report.\n \n\n\n \n Dentler, K.; Ten Teije, A.; De Keizer, N.; and Cornet, R.\n \n\n\n \n\n\n\n In Studies in Health Technology and Informatics, volume 192, pages 313--317, 2013. \n \n\n\n\n
\n\n\n \n \n \n \"BarriersPaper\n  \n \n\n \n \n doi\n  \n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Dentler2013a,\nabstract = {Today, clinical data is routinely recorded in vast amounts, but its reuse can be challenging. A secondary use that should ideally be based on previously collected clinical data is the computation of clinical quality indicators. In the present study, we attempted to retrieve all data from our hospital that is required to compute a set of quality indicators in the domain of colorectal cancer surgery. We categorised the barriers that we encountered in the scope of this project according to an existing framework, and provide recommendations on how to prevent or surmount these barriers. Assuming that our case is not unique, these recommendations might be applicable for the design, evaluation and optimisation of Electronic Health Records.},\nauthor = {Dentler, Kathrin and {Ten Teije}, Annette and {De Keizer}, Nicolette and Cornet, Ronald},\nbooktitle = {Studies in Health Technology and Informatics},\ndoi = {10.3233/978-1-61499-289-9-313},\nisbn = {9781614992882},\nissn = {09269630},\nkeywords = {Clinical Data,Data Quality,Electronic Health Record,Pragmatic Interoperability,Reuse of Data,Secondary Use of Data},\npages = {313--317},\npmid = {23920567},\ntitle = {{Barriers to the reuse of routinely recorded clinical data: A field report}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2013MedInfo2013.pdf},\nvolume = {192},\nyear = {2013}\n}\n
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\n Today, clinical data is routinely recorded in vast amounts, but its reuse can be challenging. A secondary use that should ideally be based on previously collected clinical data is the computation of clinical quality indicators. In the present study, we attempted to retrieve all data from our hospital that is required to compute a set of quality indicators in the domain of colorectal cancer surgery. We categorised the barriers that we encountered in the scope of this project according to an existing framework, and provide recommendations on how to prevent or surmount these barriers. Assuming that our case is not unique, these recommendations might be applicable for the design, evaluation and optimisation of Electronic Health Records.\n
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\n \n \n\n \n \n \n \n Identifying most relevant concepts to describe clinical trial eligibility criteria.\n \n\n\n \n Milian, K.; Bucur, A.; Harmelen, F. V.; and ten Teije, A\n \n\n\n \n\n\n\n In 6th International conference on Health Informatics (HealthInf-2013), 2013. \n \n\n\n\n
\n\n\n \n \n \n \"IdentifyingPaper\n  \n \n\n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Milian2013,\nabstract = {Since eligibility criteria of clinical trials are represented as free text, their automatic interpretation and the eval- uation of patient eligibility is challenging. Our approach to the criteria processing is based on the identification of contextual patterns and semantic concepts that together define the machine-interpretable meaning. The goal of this research is to find the most relevant concepts occurring in eligibility criteria that need to be mapped to patient record to enable automatic evaluation of patient eligibility. Based on the analysis of annotation of breast cancer trials obtained using different concept recognizers and ontologies from UMLS Thesaurus, we chose to use MetaMap and SNOMED CT to create the mapping set. To prioritize the identified concepts, we used the tf-idf measure and the corpus of over 38, 000 various clinical trials, to detect concepts specific for breast cancer, and cancer in general. The obtained results can guide the mapping order of criteria concepts to patient data. The observed substantial overlap between the terms occurring in criteria from the trials related to breast cancer and other diseases will reduce the cost of extending the trial matching system to other diseases.},\nauthor = {Milian, Krystyna and Bucur, Anca and Harmelen, Frank Van and ten Teije, A},\nbooktitle = {6th International conference on Health Informatics (HealthInf-2013)},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Milian et al. - 2013 - Identifying most relevant concepts to describe clinical trial eligibility criteria.pdf:pdf},\nisbn = {9789898565372},\ntitle = {{Identifying most relevant concepts to describe clinical trial eligibility criteria}},\nurl = {http://www.researchgate.net/publication/235946645{\\_}Identifying{\\_}most{\\_}relevant{\\_}concepts{\\_}to{\\_}describe{\\_}clinical{\\_}trial{\\_}eligibility{\\_}criteria/file/60b7d5149dcdb2f942.pdf http://www.cs.vu.nl/{~}annette/papers-pdf/2013HEALTHINF{\\_}24LONG-VERSION.pdf},\nyear = {2013}\n}\n
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\n Since eligibility criteria of clinical trials are represented as free text, their automatic interpretation and the eval- uation of patient eligibility is challenging. Our approach to the criteria processing is based on the identification of contextual patterns and semantic concepts that together define the machine-interpretable meaning. The goal of this research is to find the most relevant concepts occurring in eligibility criteria that need to be mapped to patient record to enable automatic evaluation of patient eligibility. Based on the analysis of annotation of breast cancer trials obtained using different concept recognizers and ontologies from UMLS Thesaurus, we chose to use MetaMap and SNOMED CT to create the mapping set. To prioritize the identified concepts, we used the tf-idf measure and the corpus of over 38, 000 various clinical trials, to detect concepts specific for breast cancer, and cancer in general. The obtained results can guide the mapping order of criteria concepts to patient data. The observed substantial overlap between the terms occurring in criteria from the trials related to breast cancer and other diseases will reduce the cost of extending the trial matching system to other diseases.\n
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\n \n \n\n \n \n \n \n Towards automatic patient eligibility assessment: from free-text criteria to queries.\n \n\n\n \n Milian, K.; and ten Teije, A\n \n\n\n \n\n\n\n In Artificial Intelligence in Medicine, pages 1--5, 2013. \n \n\n\n\n
\n\n\n \n \n \n \"TowardsPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Milian2013a,\nauthor = {Milian, Krystyna and ten Teije, A},\nbooktitle = {Artificial Intelligence in Medicine},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Milian, Teije - 2013 - Towards automatic patient eligibility assessment from free-text criteria to queries.pdf:pdf},\nkeywords = {cal ontologies,clinical trials,medi-,patient data representation,query generation,semantic reasoning},\npages = {1--5},\ntitle = {{Towards automatic patient eligibility assessment: from free-text criteria to queries}},\nurl = {http://link.springer.com/chapter/10.1007/978-3-642-38326-7{\\_}12 http://www.cs.vu.nl/{~}annette/papers-pdf/2013AIME-Milian.pdf},\nyear = {2013}\n}\n
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\n \n \n\n \n \n \n \n Knowledge-based patient data generation.\n \n\n\n \n Huang, Z.; van Harmelen, F.; ten Teije, A.; and Dentler, K.\n \n\n\n \n\n\n\n In Process Support and Knowledge Representation in Health Care, pages 83--96, 2013. Springer\n \n\n\n\n
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@inproceedings{Huang2013b,\nauthor = {Huang, Zhisheng and van Harmelen, Frank and ten Teije, Annette and Dentler, Kathrin},\nbooktitle = {Process Support and Knowledge Representation in Health Care},\npages = {83--96},\npublisher = {Springer},\ntitle = {{Knowledge-based patient data generation}},\nurl = {http://link.springer.com/chapter/10.1007/978-3-319-03916-9{\\_}7 http://www.cs.vu.nl/{~}annette/papers-pdf/2013KR4HCapdg.pdf},\nyear = {2013}\n}\n
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\n \n \n\n \n \n \n \n Knowledge Representation for Health-Care. (AIME 2011 Workshop KR4HC 2011), Revised Selected Papers, LNCS Volume 6924.\n \n\n\n \n Riaño, D.; ten Teije, A.; and Miksch, S.\n \n\n\n \n\n\n\n Springer, 2012.\n \n\n\n\n
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@book{Riano2012,\nauthor = {Ria{\\~{n}}o, David and ten Teije, Annette and Miksch, Silvia},\neditor = {Ria{\\~{n}}o, David and ten Teije, Annette and Miksch, Silvia},\npublisher = {Springer},\ntitle = {{Knowledge Representation for Health-Care. (AIME 2011 Workshop KR4HC 2011), Revised Selected Papers, LNCS Volume 6924}},\nurl = {http://www.springer.com/gp/book/9783642276965},\nyear = {2012}\n}\n
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\n \n \n\n \n \n \n \n The Reproducibility of CLIF, a Method for Clinical Quality Indicator Formalisation.\n \n\n\n \n Dentler, K.; Cornet, R.; ten Teije, A.; Tytgat, K.; Klinkenbijl, J.; and de Keizer, N.\n \n\n\n \n\n\n\n In Studies in Health Technology and Informatics, pages 113--117, 2012. IOS Press\n \n\n\n\n
\n\n\n \n \n \n \"ThePaper\n  \n \n\n \n \n doi\n  \n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Dentler2012a,\nauthor = {Dentler, Kathrin and Cornet, Ronald and ten Teije, Annette and Tytgat, Kristien and Klinkenbijl, Jean and de Keizer, Nicolette},\nbooktitle = {Studies in Health Technology and Informatics},\ndoi = {10.3233/978-1-61499-101-4-113},\nkeywords = {Clinical Quality Indicators,Formalisation,Knowledge Representation,SNOMED CT},\npages = {113--117},\npublisher = {IOS Press},\ntitle = {{The Reproducibility of CLIF, a Method for Clinical Quality Indicator Formalisation}},\nurl = {http://booksonline.iospress.nl/Content/View.aspx?piid=31258 http://www.cs.vu.nl/{~}annette/papers-pdf/2012MIE.pdf},\nyear = {2012}\n}\n
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\n \n \n\n \n \n \n \n Formalization of clinical trial eligibility criteria: Evaluation of a pattern-based approach.\n \n\n\n \n Milian, K.; Bucur, A.; and Teije, A T.\n \n\n\n \n\n\n\n Bioinformatics and Biomedicine \\ldots, . 2012.\n \n\n\n\n
\n\n\n \n \n \n \"FormalizationPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@article{Milian2012,\nauthor = {Milian, Krystyna and Bucur, Anca and Teije, A Ten},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Milian, Bucur, Teije - 2012 - Formalization of clinical trial eligibility criteria Evaluation of a pattern-based approach.pdf:pdf},\njournal = {Bioinformatics and Biomedicine {\\ldots}},\nkeywords = {-formalization of eligibility criteria,clinical trial recruitment,clinical trials,consider the eligibility criterion,first,for nonmelanoma skin cancer,no prior malignancy except,supporting,we detect the pattern},\ntitle = {{Formalization of clinical trial eligibility criteria: Evaluation of a pattern-based approach}},\nurl = {http://ieeexplore.ieee.org/xpls/abs{\\_}all.jsp?arnumber=6392733 http://www.cs.vu.nl/{~}annette/papers-pdf/2012BIBM.pdf},\nyear = {2012}\n}\n
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\n \n \n\n \n \n \n \n Towards the Automated Calculation of Clinical Quality Indicators.\n \n\n\n \n Dentler, K.; Ten Teije, A.; Cornet, R.; and De Keizer, N.\n \n\n\n \n\n\n\n Knowledge Representation for HealthCare, LNCS 6924: 51--64. 2012.\n \n\n\n\n
\n\n\n \n \n \n \"TowardsPaper\n  \n \n\n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n \n\n\n
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@article{Dentler2012,\nabstract = {To measure the quality of care in order to identify whether and how it can be improved is of increasing importance, and several organisations define quality indicators as tools for such measurement. The values of these quality indicators should ideally be calculated automatically based on data that is being collected during the care process. The central idea behind this paper is that quality indicators can be regarded as semantic queries that retrieve patients who fulfil certain constraints, and that indicators that are formalised as semantic queries can be calculated automatically by being run against patient data. We report our experiences in manually formalising exemplary quality indicators from natural language into SPARQL queries, and prove the concept by running the resulting queries against self-generated synthetic patient data. Both the queries and the patient data make use of SNOMED CT to represent relevant concepts. Our experimental results are promising: we ran eight queries against a dataset of 300,000 synthetically generated patients, and retrieved consistent results within acceptable time.},\nauthor = {Dentler, Kathrin and {Ten Teije}, Annette and Cornet, Ronald and {De Keizer}, Nicolette},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Dentler et al. - 2012 - Towards the Automated Calculation of Clinical Quality Indicators.pdf:pdf},\njournal = {Knowledge Representation for HealthCare},\nkeywords = {clinical data,formalisation clinical,quality indicators,semantic web reasoning,snomed ct,sparql},\npages = {51--64},\npublisher = {Springer},\ntitle = {{Towards the Automated Calculation of Clinical Quality Indicators}},\nurl = {http://www.cs.vu.nl/{~}annette/pdf/KR4HC11Dentler.pdf http://www.cs.vu.nl/{~}annette/papers-pdf/2011KR4HCDentler.pdf},\nvolume = {LNCS 6924},\nyear = {2012}\n}\n
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\n To measure the quality of care in order to identify whether and how it can be improved is of increasing importance, and several organisations define quality indicators as tools for such measurement. The values of these quality indicators should ideally be calculated automatically based on data that is being collected during the care process. The central idea behind this paper is that quality indicators can be regarded as semantic queries that retrieve patients who fulfil certain constraints, and that indicators that are formalised as semantic queries can be calculated automatically by being run against patient data. We report our experiences in manually formalising exemplary quality indicators from natural language into SPARQL queries, and prove the concept by running the resulting queries against self-generated synthetic patient data. Both the queries and the patient data make use of SNOMED CT to represent relevant concepts. Our experimental results are promising: we ran eight queries against a dataset of 300,000 synthetically generated patients, and retrieved consistent results within acceptable time.\n
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\n  \n 2011\n \n \n (5)\n \n \n
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\n \n \n\n \n \n \n \n Careflow Planning: from Time-annotated Clinical Guidelines to Temporal Hierarchical Task Networks.\n \n\n\n \n Arturo González Ferrer, Annette Ten Teije; and Juan Fdez-Olivares, K. M.\n \n\n\n \n\n\n\n In Proc. of the 13th European Conference on Artificial Intelligence in Medicine (AIME'11), 2011. Springer\n \n\n\n\n
\n\n\n \n \n \n \"CareflowPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{ArturoGonzalezFerrerAnnetteTenTeijeJuanFdez-Olivares2011,\nauthor = {{Arturo González Ferrer, Annette Ten Teije, Juan Fdez-Olivares}, Krystyna Milian},\nbooktitle = {Proc. of the 13th European Conference on Artificial Intelligence in Medicine (AIME'11)},\npublisher = {Springer},\ntitle = {{Careflow Planning: from Time-annotated Clinical Guidelines to Temporal Hierarchical Task Networks}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2011AIME.pdf},\nyear = {2011}\n}\n
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\n \n \n\n \n \n \n \n Patterns of Clinical Trial Eligibility Criteria.\n \n\n\n \n Milian, K.; ten Teije, A.; Bucur, A.; and van Harmelen, F.\n \n\n\n \n\n\n\n In The Third Knowledge Representation in Health-Care, KR4HC'11, 2011. \n \n\n\n\n
\n\n\n \n \n \n \"PatternsPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Milian2011,\nauthor = {Milian, Krystyna and ten Teije, Annette and Bucur, Anca and van Harmelen, Frank},\nbooktitle = {The Third Knowledge Representation in Health-Care, KR4HC'11},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Milian et al. - 2011 - Patterns of Clinical Trial Eligibility Criteria.pdf:pdf},\ntitle = {{Patterns of Clinical Trial Eligibility Criteria}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2011KR4HCMilian.pdf},\nyear = {2011}\n}\n
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\n \n \n\n \n \n \n \n The Semantic Web: Research and Applications 7th Extended Semantic Web Conference, ESWC 2010 Proceedings, LNCS Volume 6088, Volume 6089.\n \n\n\n \n Lora, A.; Antoniou, G.; Hyvönen, E.; ten Teije, A.; and Stuckenschmidt, H.\n , editor\n s.\n \n\n\n \n\n\n\n Springer, 2011.\n \n\n\n\n
\n\n\n \n \n \n \"ThePaper\n  \n \n\n \n\n bibtex \n \n \n \n\n  \n\n \n buy\n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@book{Lora2011,\nbooktitle = {The Semantic Web: Research and Applications 7th Extended Semantic Web Conference, ESWC 2010 Proceedings, LNCS Volume 6088, Volume 6089},\neditor = {Lora, Aroyo and Antoniou, Grigoris and Hyv{\\"{o}}nen, Eero and ten Teije, Annette and Stuckenschmidt, Heiner},\npublisher = {Springer},\ntitle = {{The Semantic Web: Research and Applications 7th Extended Semantic Web Conference, ESWC 2010 Proceedings, LNCS Volume 6088, Volume 6089}},\nurl = {http://www.springer.com/computer/communication+networks/book/978-3-642-13485-2 http://www.springer.com/computer/communication+networks/book/978-3-642-13488-3},\nyear = {2011}\n}\n
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\n \n \n\n \n \n \n \n Comparison of Reasoners for large Ontologies in the OWL 2 EL Profile.\n \n\n\n \n Kathrin Dentler, Ronald Cornet, A. t. T.; and de Keizer, N.\n \n\n\n \n\n\n\n Semantic Web Journal, . 2011.\n \n\n\n\n
\n\n\n \n \n \n \"ComparisonPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@article{KathrinDentlerRonaldCornet2011,\nauthor = {{Kathrin Dentler, Ronald Cornet}, Annette ten Teije and Nicolette de Keizer},\njournal = {Semantic Web Journal},\ntitle = {{Comparison of Reasoners for large Ontologies in the OWL 2 EL Profile}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2011SWJ.pdf},\nyear = {2011}\n}\n
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\n \n \n\n \n \n \n \n Knowledge Representation for Health-Care. Data, Processes and Guidelines (ECAI 2010 Workshop KR4HC 2010), Revised Selected Papers, LNCS Volume 6512.\n \n\n\n \n Riaño, D.; ten Teije, A.; Miksch, S.; and Peleg, M.\n , editor\n s.\n \n\n\n \n\n\n\n Springer, 2011.\n \n\n\n\n
\n\n\n \n \n \n \"KnowledgePaper\n  \n \n\n \n\n bibtex \n \n \n \n\n  \n\n \n buy\n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@book{Riano2011,\nbooktitle = {Knowledge Representation for Health-Care. Data, Processes and Guidelines (ECAI 2010 Workshop KR4HC 2010), Revised Selected Papers, LNCS Volume 6512},\neditor = {Ria{\\~{n}}o, David and ten Teije, Annette and Miksch, Silvia and Peleg, Mor},\npublisher = {Springer},\ntitle = {{Knowledge Representation for Health-Care. Data, Processes and Guidelines (ECAI 2010 Workshop KR4HC 2010), Revised Selected Papers, LNCS Volume 6512}},\nurl = {http://www.springer.com/computer/ai/book/978-3-642-18049-1http://www.springer.com/computer/ai/book/978-3-642-18049-1},\nyear = {2011}\n}\n
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\n  \n 2010\n \n \n (1)\n \n \n
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\n \n \n\n \n \n \n \n Knowledge Representation for Health-Care. Data processes and guidelines (KR4HC2009), Revised Selected Papers and Invited papers.\n \n\n\n \n David Riano; Annette ten Teije; Silvia Miksch; and Mor Peleg\n , editor\n s.\n \n\n\n \n\n\n\n Volume 5943 of LNCSSpringer, 2010.\n \n\n\n\n
\n\n\n \n \n \n \"KnowledgePaper\n  \n \n\n \n\n bibtex \n \n \n \n\n  \n\n \n buy\n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@book{DavidRiano,\neditor = {{David Riano} and {Annette ten Teije} and {Silvia Miksch} and {Mor Peleg}},\nkeywords = {medical knowledge representation},\nmendeley-tags = {medical knowledge representation},\npublisher = {Springer},\nseries = {LNCS},\ntitle = {{Knowledge Representation for Health-Care. Data processes and guidelines (KR4HC2009), Revised Selected Papers and Invited papers.}},\nurl = {http://www.springer.com/computer/database+management+{\\%}26+information+retrieval/book/978-3-642-11807-4},\nvolume = {5943},\nyear = {2010}\n}\n
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\n  \n 2009\n \n \n (9)\n \n \n
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\n \n \n\n \n \n \n \n Knowledge Engineering rediscovered: Towards Reasoning Patterns for the Semantic Web.\n \n\n\n \n Van Harmelen, F.; Ten Teije, A.; and Wache, H.\n \n\n\n \n\n\n\n In Noy, N, editor(s), Proceedings of The Fifth International Conference on Knowledge Capture 2009, pages 81--88, 2009. ACM\n \n\n\n\n
\n\n\n \n \n \n \"KnowledgePaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n  \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{VanHarmelen2009,\nauthor = {{Van Harmelen}, Frank and {Ten Teije}, Annette and Wache, Holger},\nbooktitle = {Proceedings of The Fifth International Conference on Knowledge Capture 2009},\neditor = {Noy, N},\npages = {81--88},\npublisher = {ACM},\ntitle = {{Knowledge Engineering rediscovered: Towards Reasoning Patterns for the Semantic Web}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2009KCAP.pdf http://portal.acm.org/citation.cfm?id=1597735.1597750},\nyear = {2009}\n}\n
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\n \n \n\n \n \n \n \n Reasoning about Repairability of Workflows at Design Time.\n \n\n\n \n Tagni, G; Ten Teije, A; and Van Harmelen, F\n \n\n\n \n\n\n\n In BPM 2008 Workshops 1st International Workshop on QoS in Selfhealing Web Services QSWS08 in conjunction with BPM 2008 6th International Conference on Business Process Management BMP 2008, volume 17, of LNBIP, pages 440--452, 2009. \n \n\n\n\n
\n\n\n \n \n \n \"ReasoningPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Tagni2009,\nauthor = {Tagni, G and {Ten Teije}, A and {Van Harmelen}, F},\nbooktitle = {BPM 2008 Workshops 1st International Workshop on QoS in Selfhealing Web Services QSWS08 in conjunction with BPM 2008 6th International Conference on Business Process Management BMP 2008},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Tagni, Ten Teije, Van Harmelen - 2009 - Reasoning about Repairability of Workflows at Design Time.pdf:pdf},\npages = {440--452},\nseries = {LNBIP},\ntitle = {{Reasoning about Repairability of Workflows at Design Time}},\nurl = {http://www.cs.vu.nl/{~}frankh/abstracts/BPM08-WS.html http://www.cs.vu.nl/{~}annette/papers-pdf/2008BPM-WS.pdf},\nvolume = {17},\nyear = {2009}\n}\n
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\n \n \n\n \n \n \n \n Using model checking for critiquing based on clinical guidelines.\n \n\n\n \n Groot, P.; Hommersom, A.; Lucas, P. J F; Merk, R.; ten Teije, A.; van Harmelen, F.; and Serban, R.\n \n\n\n \n\n\n\n Artificial intelligence in medicine, 46(1): 19--36. may 2009.\n \n\n\n\n
\n\n\n \n \n \n \"UsingPaper\n  \n \n\n \n \n doi\n  \n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@article{Groot2009,\nabstract = {OBJECTIVE: Medical critiquing systems compare clinical actions performed by a physician with a predefined set of actions. In order to provide useful feedback, an important task is to find differences between the actual actions and a set of 'ideal' actions as described by a clinical guideline. In case differences exist, the critiquing system provides insight into the extent to which they are compatible. METHODS AND MATERIAL: We propose a computational method for such critiquing, where the ideal actions are given by a formal model of a clinical guideline, and where the actual actions are derived from real world patient data. We employ model checking to investigate whether a part of the actual treatment is consistent with the guideline. RESULTS: We show how critiquing can be cast in terms of temporal logic, and what can be achieved by using model checking. Furthermore, a method is introduced for off-line computing relevant information which can be exploited during critiquing. The method has been applied to a clinical guideline of breast cancer in conjunction with breast cancer patient data.},\nauthor = {Groot, Perry and Hommersom, Arjen and Lucas, Peter J F and Merk, Robbert-Jan and ten Teije, Annette and van Harmelen, Frank and Serban, Radu},\ndoi = {10.1016/j.artmed.2008.07.007},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Groot et al. - 2009 - Using model checking for critiquing based on clinical guidelines.pdf:pdf},\nissn = {1873-2860},\njournal = {Artificial intelligence in medicine},\nkeywords = {Artificial Intelligence,Breast,Breast Neoplasms,Breast Neoplasms: diagnosis,Breast Neoplasms: therapy,Breast: diagnosis,Breast: therapy,Carcinoma,Clinical,Computer Simulation,Computerized,Decision Support Systems,Ductal,Female,Guideline Adherence,Humans,Logic,Medical Records Systems,Models,Patient Selection,Practice Guidelines as Topic,Systems Integration,Theoretical,Time Factors},\nmonth = {may},\nnumber = {1},\npages = {19--36},\npmid = {18824335},\ntitle = {{Using model checking for critiquing based on clinical guidelines.}},\nurl = {http://www.ncbi.nlm.nih.gov/pubmed/18824335 http://www.cs.vu.nl/{~}annette/papers-pdf/2009AIMSI.pdf},\nvolume = {46},\nyear = {2009}\n}\n
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\n OBJECTIVE: Medical critiquing systems compare clinical actions performed by a physician with a predefined set of actions. In order to provide useful feedback, an important task is to find differences between the actual actions and a set of 'ideal' actions as described by a clinical guideline. In case differences exist, the critiquing system provides insight into the extent to which they are compatible. METHODS AND MATERIAL: We propose a computational method for such critiquing, where the ideal actions are given by a formal model of a clinical guideline, and where the actual actions are derived from real world patient data. We employ model checking to investigate whether a part of the actual treatment is consistent with the guideline. RESULTS: We show how critiquing can be cast in terms of temporal logic, and what can be achieved by using model checking. Furthermore, a method is introduced for off-line computing relevant information which can be exploited during critiquing. The method has been applied to a clinical guideline of breast cancer in conjunction with breast cancer patient data.\n
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\n \n \n\n \n \n \n \n The Free Speech Engine Conversational web service compatibility for free.\n \n\n\n \n Stegers, R.; Harmelen, F. V.; and Teije, A.\n \n\n\n \n\n\n\n In International Conference on Semantic Web and Web Services (SWWS'09), 2009. \n \n\n\n\n
\n\n\n \n \n \n \"ThePaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Stegers2009,\nauthor = {Stegers, Ruud and Harmelen, Frank Van and Teije, Annette},\nbooktitle = {International Conference on Semantic Web and Web Services (SWWS'09)},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Stegers, Harmelen, Teije - 2009 - The Free Speech Engine Conversational web service compatibility for free.pdf:pdf},\nkeywords = {interoperability,protocol,web services},\ntitle = {{The Free Speech Engine Conversational web service compatibility for free}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2009SWWS.pdf},\nyear = {2009}\n}\n
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\n \n \n\n \n \n \n \n Identifying Disease-centric Subdomains in Very Large Medical Ontologies, a Case-study on Breast-cancer Concepts in SNOMED.\n \n\n\n \n Miliana, K.; Aleksovskib, Z.; Vdovjakb, R.; ten Teijea, A.; and van Harmelena, F.\n \n\n\n \n\n\n\n In BNAIC, 2009. Citeseer\n \n\n\n\n
\n\n\n \n \n \n \"IdentifyingPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Miliana2009,\nauthor = {Miliana, K. and Aleksovskib, Z. and Vdovjakb, R. and ten Teijea, A. and van Harmelena, F.},\nbooktitle = {BNAIC},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Miliana et al. - 2009 - Identifying Disease-centric Subdomains in Very Large Medical Ontologies, a Case-study on Breast-cancer Concepts.pdf:pdf},\npublisher = {Citeseer},\ntitle = {{Identifying Disease-centric Subdomains in Very Large Medical Ontologies, a Case-study on Breast-cancer Concepts in SNOMED}},\nurl = {http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.148.2287{\\&}rep=rep1{\\&}type=pdf http://www.cs.vu.nl/{~}annette/papers-pdf/2009BNAIC-KR4HC.pdf},\nyear = {2009}\n}\n
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\n \n \n\n \n \n \n \n MARVIN: A platform for large-scale analysis of Semantic Web data.\n \n\n\n \n Oren, E.; Kotoulas, S.; Anadiotis, G.; Siebes, R.; Ten Teije, A.; and Van Harmelen, F.\n \n\n\n \n\n\n\n In Proceeding of the WebSci09 Society OnLine, 2009. \n \n\n\n\n
\n\n\n \n \n \n \"MARVIN:Paper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Oren2009,\nauthor = {Oren, Eyal and Kotoulas, Spyros and Anadiotis, George and Siebes, Ronny and {Ten Teije}, Annette and {Van Harmelen}, Frank},\nbooktitle = {Proceeding of the WebSci09 Society OnLine},\nissn = {15708268},\ntitle = {{MARVIN: A platform for large-scale analysis of Semantic Web data}},\nurl = {http://www.few.vu.nl/{~}kot/papers/marvin.pdf http://www.cs.vu.nl/{~}annette/papers-pdf/2009websci.pdf},\nyear = {2009}\n}\n
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\n \n \n\n \n \n \n \n Marvin: Distributed reasoning over large-scale Semantic Web data.\n \n\n\n \n Oren, E.; Kotoulas, S.; Anadiotis, G.; Siebes, R.; ten Teije, A.; and van Harmelen, F.\n \n\n\n \n\n\n\n Journal of Web Semantics, 7(4): 305--316. 2009.\n \n\n\n\n
\n\n\n \n \n \n \"Marvin:Paper\n  \n \n\n \n \n doi\n  \n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n \n\n\n
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@article{Oren2009b,\nabstract = {Many Semantic Web problems are difficult to solve through common divide-and-conquer strategies, since they are hard to partition. We present Marvin, a parallel and distributed platform for processing large amounts of RDF data, on a network of loosely coupled peers. We present our divide-conquer-swap strategy and show that this model converges towards completeness. Within this strategy, we address the problem of making distributed reasoning scalable and load-balanced. We present SpeedDate, a routing strategy that combines data clustering with random exchanges. The random exchanges ensure load balancing, while the data clustering attempts to maximise efficiency. SpeedDate is compared against random and deterministic (DHT-like) approaches, on performance and load-balancing. We simulate parameters such as system size, data distribution, churn rate, and network topology. The results indicate that SpeedDate is near-optimally balanced, performs in the same order of magnitude as a DHT-like approach, and has an average throughput per node that scales with sqrt(i) for i items in the system. We evaluate our overall Marvin system for performance, scalability, load balancing and efficiency. {\\textcopyright} 2009 Elsevier B.V. All rights reserved.},\nauthor = {Oren, Eyal and Kotoulas, Spyros and Anadiotis, George and Siebes, Ronny and ten Teije, Annette and van Harmelen, Frank},\ndoi = {10.1016/j.websem.2009.09.002},\nisbn = {1570-8268},\nissn = {15708268},\njournal = {Journal of Web Semantics},\nkeywords = {Distributed,Load-balancing,Reasoning,Scalability},\nnumber = {4},\npages = {305--316},\ntitle = {{Marvin: Distributed reasoning over large-scale Semantic Web data}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2009JWS.pdf},\nvolume = {7},\nyear = {2009}\n}\n
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\n Many Semantic Web problems are difficult to solve through common divide-and-conquer strategies, since they are hard to partition. We present Marvin, a parallel and distributed platform for processing large amounts of RDF data, on a network of loosely coupled peers. We present our divide-conquer-swap strategy and show that this model converges towards completeness. Within this strategy, we address the problem of making distributed reasoning scalable and load-balanced. We present SpeedDate, a routing strategy that combines data clustering with random exchanges. The random exchanges ensure load balancing, while the data clustering attempts to maximise efficiency. SpeedDate is compared against random and deterministic (DHT-like) approaches, on performance and load-balancing. We simulate parameters such as system size, data distribution, churn rate, and network topology. The results indicate that SpeedDate is near-optimally balanced, performs in the same order of magnitude as a DHT-like approach, and has an average throughput per node that scales with sqrt(i) for i items in the system. We evaluate our overall Marvin system for performance, scalability, load balancing and efficiency. \\textcopyright 2009 Elsevier B.V. All rights reserved.\n
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\n \n \n\n \n \n \n \n Exploiting thesauri knowledge in medical guideline formalization.\n \n\n\n \n Serban, R; and Ten Teije, A.\n \n\n\n \n\n\n\n Methods of Information in Medicine, 48(5): 468--474. 2009.\n \n\n\n\n
\n\n\n \n \n \n \"ExploitingPaper\n  \n \n\n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@article{Serban2009,\nabstract = {OBJECTIVES: As in software product lifecycle, the effort spent in maintaining medical knowledge in guidelines can be reduced, if modularization, formalization and tracking of domain knowledge are employed across the guideline development phases. METHODS: We propose to exploit and combine knowledge templates with medical background knowledge from existing thesauri in order to produce reusable building blocks used in guideline development. These templates enable easier guideline formalization, by describing how chunks of medical knowledge can be combined into more complex ones and how they are linked to a textual representation. RESULTS: By linking our ontology used in guideline formalization with existing thesauri, we can use compilations of thesauri knowledge as building blocks for modeling and maintaining the content of a medical guideline. CONCLUSIONS: Our paper investigates whether medical knowledge acquired from several medical thesauri can be molded on a guideline pattern, such that it supports building of executable models of guidelines.},\nauthor = {Serban, R and {Ten Teije}, Annete},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Serban, Ten Teije - 2009 - Exploiting thesauri knowledge in medical guideline formalization.pdf:pdf},\ninstitution = {Vrije Universiteit, Faculty of Exact Sciences, 1081 HV Amsterdam, The Netherlands.},\njournal = {Methods of Information in Medicine},\nnumber = {5},\npages = {468--474},\npmid = {19448889},\ntitle = {{Exploiting thesauri knowledge in medical guideline formalization.}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2009MIM.pdf},\nvolume = {48},\nyear = {2009}\n}\n
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\n OBJECTIVES: As in software product lifecycle, the effort spent in maintaining medical knowledge in guidelines can be reduced, if modularization, formalization and tracking of domain knowledge are employed across the guideline development phases. METHODS: We propose to exploit and combine knowledge templates with medical background knowledge from existing thesauri in order to produce reusable building blocks used in guideline development. These templates enable easier guideline formalization, by describing how chunks of medical knowledge can be combined into more complex ones and how they are linked to a textual representation. RESULTS: By linking our ontology used in guideline formalization with existing thesauri, we can use compilations of thesauri knowledge as building blocks for modeling and maintaining the content of a medical guideline. CONCLUSIONS: Our paper investigates whether medical knowledge acquired from several medical thesauri can be molded on a guideline pattern, such that it supports building of executable models of guidelines.\n
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\n \n \n\n \n \n \n \n Identifying Disease-centric Subdomains in Very Large Medical Ontologies, a Case-study on Breast-cancer Concepts in SNOMED.\n \n\n\n \n Milian, K.; Aleksovski, Z.; Vdovjak, R.; ten Teije, A.; and van Harmelen, F.\n \n\n\n \n\n\n\n In ten Teije, A.; Riaño, D.; Miksch, S.; and Peleg, M., editor(s), KR4HC 2009, pages 41----50, 2009. Citeseer\n \n\n\n\n
\n\n\n \n \n \n \"IdentifyingPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Milian2009,\nauthor = {Milian, K. and Aleksovski, Z. and Vdovjak, R. and ten Teije, A. and van Harmelen, F.},\nbooktitle = {KR4HC 2009},\neditor = {ten Teije, Annette and Ria{\\~{n}}o, David and Miksch, Silvia and Peleg, Mor},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Milian et al. - 2009 - Identifying Disease-centric Subdomains in Very Large Medical Ontologies, a Case-study on Breast-cancer Concepts i.pdf:pdf},\npages = {41----50},\npublisher = {Citeseer},\ntitle = {{Identifying Disease-centric Subdomains in Very Large Medical Ontologies, a Case-study on Breast-cancer Concepts in SNOMED}},\nurl = {http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.148.2287{\\&}rep=rep1{\\&}type=pdf http://www.cs.vu.nl/{~}annette/papers-pdf/2009KR4HC.pdf},\nyear = {2009}\n}\n
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\n  \n 2008\n \n \n (2)\n \n \n
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\n \n \n\n \n \n \n \n COMPUTER-BASED MEDICAL GUIDELINES AND PROTOCOLS : A PRIMER AND CURRENT TRENDS Studies in Health Technology and Informatics.\n \n\n\n \n Ten Teije, A; Miksch, S; and Lucas, P\n \n\n\n \n\n\n\n Volume 139 IOS Press, 2008.\n \n\n\n\n
\n\n\n \n \n \n \"COMPUTER-BASEDPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n  \n\n \n buy\n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@book{TenTeije2008,\nauthor = {{Ten Teije}, A and Miksch, S and Lucas, P},\nbooktitle = {Horizon},\nisbn = {1586038737},\npages = {300},\npublisher = {IOS Press},\ntitle = {{COMPUTER-BASED MEDICAL GUIDELINES AND PROTOCOLS : A PRIMER AND CURRENT TRENDS Studies in Health Technology and Informatics}},\nurl = {http://www.booksonline.iospress.nl/Content/View.aspx?piid=9732},\nvolume = {139},\nyear = {2008}\n}\n
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\n \n \n\n \n \n \n \n WS-DIAMOND: Web Services–DIAgnosability, MONitoring and Diagnosis.\n \n\n\n \n Console, L.; and Team, W.\n \n\n\n \n\n\n\n In At your service: Service Engineering in the Information Society Technologies Program. MIT press, 2008.\n \n\n\n\n
\n\n\n \n \n \n \"WS-DIAMOND:Paper\n  \n \n\n \n\n bibtex \n \n \n \n\n  \n\n \n buy\n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@incollection{Console2008,\nauthor = {Console, Luca and Team, WS-DIAMOND},\nbooktitle = {At your service: Service Engineering in the Information Society Technologies Program},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Console, Team - 2008 - WS-DIAMOND Web Services–DIAgnosability, MONitoring and Diagnosis.pdf:pdf},\npublisher = {MIT press},\ntitle = {{WS-DIAMOND: Web Services–DIAgnosability, MONitoring and Diagnosis}},\nurl = {http://scholar.google.com/scholar?hl=en{\\&}btnG=Search{\\&}q=intitle:WS-DIAMOND:+Web+Services?DIAgnosability,+MONitoring,+and+Diagnosis{\\#}1 http://www.cs.vu.nl/{~}annette/papers-pdf/2008DIAMOND-CH08.pdf},\nyear = {2008}\n}\n
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\n  \n 2007\n \n \n (4)\n \n \n
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\n \n \n\n \n \n \n \n Extraction and use of linguistic patterns for modelling medical guidelines.\n \n\n\n \n Serban, R.; Ten Teije, A.; Van Harmelen, F.; Marcos, M.; and Polo-Conde, C.\n \n\n\n \n\n\n\n Artificial Intelligence in Medicine, 39(2): 137--149. 2007.\n \n\n\n\n
\n\n\n \n \n \n \"ExtractionPaper\n  \n \n\n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@article{Serban2007,\nabstract = {OBJECTIVE: The quality of knowledge updates in evidence-based medical guidelines can be improved and the effort spent for updating can be reduced if the knowledge underlying the guideline text is explicitly modelled using the so-called linguistic guideline patterns, mappings between a text fragment and a formal representation of its corresponding medical knowledge. METHODS AND MATERIAL: Ontology-driven extraction of linguistic patterns is a method to automatically reconstruct the control knowledge captured in guidelines, which facilitates a more effective modelling and authoring of medical guidelines. We illustrate by examples the use of this method for generating and instantiating linguistic patterns in the text of a guideline for treatment of breast cancer, and evaluate the usefulness of these patterns in the modelling of this guideline. RESULTS: We developed a methodology for extracting and using linguistic patterns in guideline formalization, to aid the human modellers in guideline formalization and reduce the human modelling effort. Using automatic transformation rules for simple linguistic patterns, a good recall (between 72{\\%} and 80{\\%}) is obtained in selecting the procedural knowledge relevant for the guideline model, even though the precision of the guideline model generated automatically covers only between 20{\\%} and 35{\\%} of the human-generated guideline model. These results indicate the suitability of our method as a pre-processing step in medical guideline formalization. CONCLUSIONS: Modelling and authoring of medical texts can benefit from our proposed method. As pre-requisites for generating automatically a skeleton of the guideline model from the procedural part of the guideline text, to aid the human modeller, the medical terminology used by the guideline must have a good overlap with existing medical thesauri and its procedural knowledge must obey linguistic regularities that can be mapped into the control constructs of the target guideline modelling language.},\nauthor = {Serban, Radu and {Ten Teije}, Annette and {Van Harmelen}, Frank and Marcos, Mar and Polo-Conde, Cristina},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Serban et al. - 2007 - Extraction and use of linguistic patterns for modelling medical guidelines.pdf:pdf},\ninstitution = {Artificial Intelligence Department, Vrije Universiteit, De Boelelaan 1081a, 1081HV Amsterdam, The Netherlands. serbanr@few.vu.nl},\njournal = {Artificial Intelligence in Medicine},\nnumber = {2},\npages = {137--149},\npmid = {16963241},\ntitle = {{Extraction and use of linguistic patterns for modelling medical guidelines.}},\nurl = {http://www.ncbi.nlm.nih.gov/pubmed/16963241 http://www.cs.vu.nl/{~}annette/papers-pdf/2007AIM.pdf},\nvolume = {39},\nyear = {2007}\n}\n
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\n OBJECTIVE: The quality of knowledge updates in evidence-based medical guidelines can be improved and the effort spent for updating can be reduced if the knowledge underlying the guideline text is explicitly modelled using the so-called linguistic guideline patterns, mappings between a text fragment and a formal representation of its corresponding medical knowledge. METHODS AND MATERIAL: Ontology-driven extraction of linguistic patterns is a method to automatically reconstruct the control knowledge captured in guidelines, which facilitates a more effective modelling and authoring of medical guidelines. We illustrate by examples the use of this method for generating and instantiating linguistic patterns in the text of a guideline for treatment of breast cancer, and evaluate the usefulness of these patterns in the modelling of this guideline. RESULTS: We developed a methodology for extracting and using linguistic patterns in guideline formalization, to aid the human modellers in guideline formalization and reduce the human modelling effort. Using automatic transformation rules for simple linguistic patterns, a good recall (between 72% and 80%) is obtained in selecting the procedural knowledge relevant for the guideline model, even though the precision of the guideline model generated automatically covers only between 20% and 35% of the human-generated guideline model. These results indicate the suitability of our method as a pre-processing step in medical guideline formalization. CONCLUSIONS: Modelling and authoring of medical texts can benefit from our proposed method. As pre-requisites for generating automatically a skeleton of the guideline model from the procedural part of the guideline text, to aid the human modeller, the medical terminology used by the guideline must have a good overlap with existing medical thesauri and its procedural knowledge must obey linguistic regularities that can be mapped into the control constructs of the target guideline modelling language.\n
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\n \n \n\n \n \n \n \n Maintaining Formal Models of Living Guidelines Efficiently.\n \n\n\n \n Seyfang, A.; Wittenberg, J.; Miksch, S.; Marcos, M.; Teije, A.; and Rosenbrand, K.\n \n\n\n \n\n\n\n In Proceedings of the Eleventh European Conference on Artificial Intelligence in Medicine (AIME'07) LNAI, 2007. Springer Verlag\n \n\n\n\n
\n\n\n \n \n \n \"MaintainingPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Seyfang2007,\nauthor = {Seyfang, Andreas and Wittenberg, Jolanda and Miksch, Silvia and Marcos, Mar and Teije, Annette and Rosenbrand, Kitty},\nbooktitle = {Proceedings of the Eleventh European Conference on Artificial Intelligence in Medicine (AIME'07) LNAI},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Seyfang et al. - 2007 - Maintaining Formal Models of Living Guidelines Efficiently.pdf:pdf},\npublisher = {Springer Verlag},\ntitle = {{Maintaining Formal Models of Living Guidelines Efficiently}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2007AIMESeyfang.pdf},\nyear = {2007}\n}\n
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\n \n \n\n \n \n \n \n The role of model checking in critiquing based on clinical guidelines.\n \n\n\n \n Groot, P; Hommersom, A; Lucas, P; Serban, R; Ten Teije, A; and Van Harmelen, F\n \n\n\n \n\n\n\n In Proceedings of the Eleventh European Conference on Artificial Intelligence in Medicine (AIME'07), LNAI, volume 4594 LNAI, pages 411--420, 2007. Springer Verlag\n \n\n\n\n
\n\n\n \n \n \n \"ThePaper\n  \n \n\n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
\n
@inproceedings{Groot2007,\nabstract = {Medical critiquing systems criticise clinical actions performed by a physician. In order to provide useful feedback, an important task is to find differences between the actual actions and a set of 'ideal' actions as described by a clinical guideline. In case differences exist, insight to which extent they are compatible is provided by the critiquing system. We propose a methodology for such critiquing, where the ideal actions are given by a formal model of a clinical guideline, and where the actual actions are derived from real world patient data. We employ model checking to investigate whether a part of the actual treatment is consistent with the guideline. Furthermore, it is shown how critiquing can be cast in terms of temporal logic, and what can be achieved by using model checking. The methodology has been applied to a clinical guideline of breast cancer in conjunction with breast cancer patient data. Springer-Verlag Berlin Heidelberg 2007.},\nauthor = {Groot, P and Hommersom, A and Lucas, P and Serban, R and {Ten Teije}, A and {Van Harmelen}, F},\nbooktitle = {Proceedings of the Eleventh European Conference on Artificial Intelligence in Medicine (AIME'07), LNAI},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Groot et al. - 2007 - The role of model checking in critiquing based on clinical guidelines.pdf:pdf},\npages = {411--420},\npublisher = {Springer Verlag},\ntitle = {{The role of model checking in critiquing based on clinical guidelines}},\nurl = {http://www.scopus.com/scopus/inward/record.url?eid=2-s2.0-35148864030{\\&}partnerID=40{\\&}rel=R8.2.0 http://www.cs.vu.nl/{~}annette/papers-pdf/2007AIMEGroot.pdf},\nvolume = {4594 LNAI},\nyear = {2007}\n}\n
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\n Medical critiquing systems criticise clinical actions performed by a physician. In order to provide useful feedback, an important task is to find differences between the actual actions and a set of 'ideal' actions as described by a clinical guideline. In case differences exist, insight to which extent they are compatible is provided by the critiquing system. We propose a methodology for such critiquing, where the ideal actions are given by a formal model of a clinical guideline, and where the actual actions are derived from real world patient data. We employ model checking to investigate whether a part of the actual treatment is consistent with the guideline. Furthermore, it is shown how critiquing can be cast in terms of temporal logic, and what can be achieved by using model checking. The methodology has been applied to a clinical guideline of breast cancer in conjunction with breast cancer patient data. Springer-Verlag Berlin Heidelberg 2007.\n
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\n \n \n\n \n \n \n \n Anytime Classification by Ontology Approximation.\n \n\n\n \n Schlobach, S; Blaauw, E; Kebir, M E.; Ten Teije, A; Van Harmelen, F; Bortoli, S; Hobbelman, M; Millian, K; Ren, Y; Stam, S; Thomassen, P; Van Het Schip, R; and Van Willigem, W\n \n\n\n \n\n\n\n In Piskac, R., editor(s), Proceedings of the workshop on new forms of reasoning for the Semantic Web scalable tolerant and dynamic, pages 60--74, 2007. \n \n\n\n\n
\n\n\n \n \n \n \"AnytimePaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Schlobach2007,\nauthor = {Schlobach, S and Blaauw, E and Kebir, M El and {Ten Teije}, A and {Van Harmelen}, F and Bortoli, S and Hobbelman, M and Millian, K and Ren, Y and Stam, S and Thomassen, P and {Van Het Schip}, R and {Van Willigem}, W},\nbooktitle = {Proceedings of the workshop on new forms of reasoning for the Semantic Web scalable tolerant and dynamic},\neditor = {Piskac, Ruzica},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Schlobach et al. - 2007 - Anytime Classification by Ontology Approximation.pdf:pdf},\npages = {60--74},\ntitle = {{Anytime Classification by Ontology Approximation}},\nurl = {http://www.cs.vu.nl/{~}frankh/abstracts/ISWC07-WS.html http://www.cs.vu.nl/{~}annette/papers-pdf/2007ISWC-WS.pdf},\nyear = {2007}\n}\n
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\n  \n 2006\n \n \n (5)\n \n \n
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\n \n \n\n \n \n \n \n Improving medical protocols by formal methods.\n \n\n\n \n ten Teije, A.; Marcos, M.; Balser, M.; van Croonenborg, J.; Duelli, C.; van Harmelen, F.; Lucas, P.; Miksch, S.; Reif, W.; Rosenbrand, K.; and Seyfang, A.\n \n\n\n \n\n\n\n Artificial intelligence in medicine, 36(3): 193--209. mar 2006.\n \n\n\n\n
\n\n\n \n \n \n \"ImprovingPaper\n  \n \n\n \n \n doi\n  \n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
\n
@article{TenTeije2006,\nabstract = {OBJECTIVES: During the last decade, evidence-based medicine has given rise to an increasing number of medical practice guidelines and protocols. However, the work done on developing and distributing protocols outweighs the efforts on guaranteeing their quality. Indeed, anomalies like ambiguity and incompleteness are frequent in medical protocols. Recent efforts have tried to address the problem of protocol improvement, but they are not sufficient since they rely on informal processes and notations. Our objective is to improve the quality of medical protocols. APPROACH: The solution we suggest to the problem of quality improvement of protocols consists in the utilisation of formal methods. It requires the definition of an adequate protocol representation language, the development of techniques for the formal analysis of protocols described in that language and, more importantly, the evaluation of the feasibility of the approach based on the formalisation and verification of real-life medical protocols. For the first two aspects we rely on earlier work from the fields of knowledge representation and formal methods. The third aspect, i.e. the evaluation of the use of formal methods in the quality improvement of protocols, constitutes our main objective. The steps with which we have carried out this evaluation are the following: (1) take two real-life reference protocols which cover a wide variety of protocol characteristics; (2) formalise these reference protocols; (3) check the formalisation for the verification of interesting protocol properties; and (4) determine how many errors can be uncovered in this way. RESULTS: Our main results are: a consolidated formal language to model medical practice protocols; two protocols, each both modelled and formalised; a list of properties that medical protocols should satisfy; verification proofs for these protocols and properties; and perspectives of the potentials of this approach. Our results have been evaluated by a panel of medical experts, who judged that the problems we detected in the protocols with the help of formal methods were serious and should be avoided. CONCLUSIONS: We have succeeded in demonstrating the feasibility of formal methods for improving medical protocols.},\nauthor = {ten Teije, Annette and Marcos, Mar and Balser, Michel and van Croonenborg, Joyce and Duelli, Christoph and van Harmelen, Frank and Lucas, Peter and Miksch, Silvia and Reif, Wolfgang and Rosenbrand, Kitty and Seyfang, Andreas},\ndoi = {10.1016/j.artmed.2005.10.006},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/ten Teije et al. - 2006 - Improving medical protocols by formal methods.pdf:pdf},\nissn = {0933-3657},\njournal = {Artificial intelligence in medicine},\nkeywords = {Artificial Intelligence,Clinical Protocols,Feasibility Studies,Health Care,Humans,Infant,Jaundice,Neonatal,Neonatal: therapy,Newborn,Practice Guidelines as Topic,Programming Languages,Quality Assurance},\nmonth = {mar},\nnumber = {3},\npages = {193--209},\npmid = {16376061},\ntitle = {{Improving medical protocols by formal methods.}},\nurl = {http://www.ncbi.nlm.nih.gov/pubmed/16376061 http://www.cs.vu.nl/{~}annette/papers-pdf/2006AIIM.pdf},\nvolume = {36},\nyear = {2006}\n}\n
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\n OBJECTIVES: During the last decade, evidence-based medicine has given rise to an increasing number of medical practice guidelines and protocols. However, the work done on developing and distributing protocols outweighs the efforts on guaranteeing their quality. Indeed, anomalies like ambiguity and incompleteness are frequent in medical protocols. Recent efforts have tried to address the problem of protocol improvement, but they are not sufficient since they rely on informal processes and notations. Our objective is to improve the quality of medical protocols. APPROACH: The solution we suggest to the problem of quality improvement of protocols consists in the utilisation of formal methods. It requires the definition of an adequate protocol representation language, the development of techniques for the formal analysis of protocols described in that language and, more importantly, the evaluation of the feasibility of the approach based on the formalisation and verification of real-life medical protocols. For the first two aspects we rely on earlier work from the fields of knowledge representation and formal methods. The third aspect, i.e. the evaluation of the use of formal methods in the quality improvement of protocols, constitutes our main objective. The steps with which we have carried out this evaluation are the following: (1) take two real-life reference protocols which cover a wide variety of protocol characteristics; (2) formalise these reference protocols; (3) check the formalisation for the verification of interesting protocol properties; and (4) determine how many errors can be uncovered in this way. RESULTS: Our main results are: a consolidated formal language to model medical practice protocols; two protocols, each both modelled and formalised; a list of properties that medical protocols should satisfy; verification proofs for these protocols and properties; and perspectives of the potentials of this approach. Our results have been evaluated by a panel of medical experts, who judged that the problems we detected in the protocols with the help of formal methods were serious and should be avoided. CONCLUSIONS: We have succeeded in demonstrating the feasibility of formal methods for improving medical protocols.\n
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\n \n \n\n \n \n \n \n Modelling Web Service Composition for Deductive Web Mining.\n \n\n\n \n Svátek, V.; Vacura, M.; Labský, M.; and Ten Teije, A.\n \n\n\n \n\n\n\n Computing and Informatics, 22: 1001--1024. 2006.\n \n\n\n\n
\n\n\n \n \n \n \"ModellingPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@article{Svatek2006,\nauthor = {Sv{\\'{a}}tek, Vojtech and Vacura, Miroslav and Labsk{\\'{y}}, Martin and {Ten Teije}, Annette},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Sv{\\'{a}}tek et al. - 2006 - Modelling Web Service Composition for Deductive Web Mining.pdf:pdf},\njournal = {Computing and Informatics},\nkeywords = {ontologies,problem-solving methods,web mining,web services},\npages = {1001--1024},\ntitle = {{Modelling Web Service Composition for Deductive Web Mining}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2006CAI.pdf},\nvolume = {22},\nyear = {2006}\n}\n
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\n \n \n\n \n \n \n \n Formalization of medical guidelines exploiting medical thesauri.\n \n\n\n \n Serban, R.; and Ten Teije, A.\n \n\n\n \n\n\n\n In Reichert, A.; Mihalas, G; and Stoicu-Tivadar, L, editor(s), Proceedings of the European Federation for Medical Informatics Special Topic Conference, pages 368--86, 2006. IOS Press\n \n\n\n\n
\n\n\n \n \n \n \"FormalizationPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Serban2006a,\nauthor = {Serban, Radu and {Ten Teije}, Annette},\nbooktitle = {Proceedings of the European Federation for Medical Informatics Special Topic Conference},\neditor = {Reichert, Assa and Mihalas, G and Stoicu-Tivadar, L},\nisbn = {1586036149},\npages = {368--86},\npublisher = {IOS Press},\ntitle = {{Formalization of medical guidelines exploiting medical thesauri}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2006FCTC.pdf},\nyear = {2006}\n}\n
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\n \n \n\n \n \n \n \n From Natural Language to Formal Proof Goal.\n \n\n\n \n Stegers, R.; Ten Teije, A.; and Van Harmelen, F.\n \n\n\n \n\n\n\n In Proceedings of the 15th International Conference on Knowledge Engineering and Knowledge Management (\\EKAW\\'06) LNAI 4248, volume 4248, of Lecture Notes in Computer Science, pages 51--59, 2006. Springer Berlin Heidelberg\n \n\n\n\n
\n\n\n \n \n \n \"FromPaper\n  \n \n\n \n \n doi\n  \n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Stegers2006,\nauthor = {Stegers, Ruud and {Ten Teije}, Annette and {Van Harmelen}, Frank},\nbooktitle = {Proceedings of the 15th International Conference on Knowledge Engineering and Knowledge Management ({\\{}EKAW{\\}}'06) LNAI 4248},\ndoi = {10.1007/11891451},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Stegers, Ten Teije, Van Harmelen - 2006 - From Natural Language to Formal Proof Goal.pdf:pdf},\nisbn = {9783540463634},\npages = {51--59},\npublisher = {Springer Berlin Heidelberg},\nseries = {Lecture Notes in Computer Science},\ntitle = {{From Natural Language to Formal Proof Goal}},\nurl = {http://dblp.uni-trier.de/db/conf/ekaw/ekaw2006.html{\\#}StegersTH06 http://www.cs.vu.nl/{~}annette/papers-pdf/2006EKAW.pdf},\nvolume = {4248},\nyear = {2006}\n}\n
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\n \n \n\n \n \n \n \n Incremental guideline formalization with tool support.\n \n\n\n \n Serban, R; Puig-Centelles, A; and Ten Teije, A\n \n\n\n \n\n\n\n In Proceedings of the 3rd IFIP Conference on Artificial Intelligence Applications and Innovations (AIAI 2006), pages 106--118, 2006. \n \n\n\n\n
\n\n\n \n \n \n \"IncrementalPaper\n  \n \n\n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Serban2006,\nabstract = {Guideline formalization is recognized as an important component in improving computerized guidelines, which in turn leads to better informedness, lower inter-practician variability and, ultimately, to higher quality healthcare. By means of a modeling exercise, we investigate the role of guideline formalization tools which use two different knowledge transformation principles in producing re-usable knowledge objects useful for representing medical processes and performing updates of medical guidelines. We give a general evaluation of usefulness and state the main requirements for tools that reuse medical knowledge and support authoring of guidelines. 2006 International Federation for Information Processing.},\nauthor = {Serban, R and Puig-Centelles, A and {Ten Teije}, A},\nbooktitle = {Proceedings of the 3rd IFIP Conference on Artificial Intelligence Applications and Innovations (AIAI 2006)},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Serban, Puig-Centelles, Ten Teije - 2006 - Incremental guideline formalization with tool support.pdf:pdf},\npages = {106--118},\ntitle = {{Incremental guideline formalization with tool support}},\nurl = {http://www.scopus.com/scopus/inward/record.url?eid=2-s2.0-33749126525{\\&}partnerID=40{\\&}rel=R8.2.0 http://www.cs.vu.nl/{~}annette/papers-pdf/2006AIAI.pdf},\nyear = {2006}\n}\n
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\n Guideline formalization is recognized as an important component in improving computerized guidelines, which in turn leads to better informedness, lower inter-practician variability and, ultimately, to higher quality healthcare. By means of a modeling exercise, we investigate the role of guideline formalization tools which use two different knowledge transformation principles in producing re-usable knowledge objects useful for representing medical processes and performing updates of medical guidelines. We give a general evaluation of usefulness and state the main requirements for tools that reuse medical knowledge and support authoring of guidelines. 2006 International Federation for Information Processing.\n
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\n \n \n\n \n \n \n \n Reasoning with Inconsistent Ontologies.\n \n\n\n \n Huang, Z.; Van Harmelen, F; and Ten Teije, A\n \n\n\n \n\n\n\n In Kaelbling, L. P.; and Saffiotti, A., editor(s), Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence IJCAI05, pages 454--459, 2005. \n \n\n\n\n
\n\n\n \n \n \n \"ReasoningPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Huang2005a,\nauthor = {Huang, Zhisheng and {Van Harmelen}, F and {Ten Teije}, A},\nbooktitle = {Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence IJCAI05},\neditor = {Kaelbling, Leslie Pack and Saffiotti, Alessandro},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Huang, Van Harmelen, Ten Teije - 2005 - Reasoning with Inconsistent Ontologies.pdf:pdf},\npages = {454--459},\ntitle = {{Reasoning with Inconsistent Ontologies}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2005IJCAI.pdf},\nyear = {2005}\n}\n
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\n \n \n\n \n \n \n \n Ontology-driven extraction of guideline patterns Evaluating the use of patterns in guideline formalization Conclusions.\n \n\n\n \n Serban, R.; Ten Teije, A.; Harmelen, F. V.; Marcos, M.; and Polo-conde, C.\n \n\n\n \n\n\n\n In Proceedings of the Seventeenth Belgian/Dutch Conference on AI, pages 1--2, Brussel, 2005. \n \n\n\n\n
\n\n\n \n \n \n \"Ontology-drivenPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Serban,\naddress = {Brussel},\nauthor = {Serban, Radu and {Ten Teije}, Annette and Harmelen, Frank Van and Marcos, Mar and Polo-conde, Cristina},\nbooktitle = {Proceedings of the Seventeenth Belgian/Dutch Conference on AI},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Serban et al. - Unknown - Ontology-driven extraction of guideline patterns Evaluating the use of patterns in guideline formalization Con.pdf:pdf},\npages = {1--2},\ntitle = {{Ontology-driven extraction of guideline patterns Evaluating the use of patterns in guideline formalization Conclusions}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2005BNAICRS.pdf},\nyear = {2005}\n}\n
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\n \n \n\n \n \n \n \n Formalising medical quality indicators to improve guidelines.\n \n\n\n \n Van Gendt, M.; Ten Teije, A.; Serban, R.; and Van Harmelen, F.\n \n\n\n \n\n\n\n In Miksch, S.; Hunter, J.; and Keravnou, E., editor(s), Proceedings of the 10th European Conference on Artificial Intelligence in Medicine (\\AIME\\-05) LNAI 3581, pages 201--210, 2005. Springer\n \n\n\n\n
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@inproceedings{VanGendt2005,\nauthor = {{Van Gendt}, M. and {Ten Teije}, A. and Serban, Radu and {Van Harmelen}, F.},\nbooktitle = {Proceedings of the 10th European Conference on Artificial Intelligence in Medicine ({\\{}AIME{\\}}-05) LNAI 3581},\neditor = {Miksch, Silvia and Hunter, Jim and Keravnou, Elpida},\npages = {201--210},\npublisher = {Springer},\ntitle = {{Formalising medical quality indicators to improve guidelines}},\nurl = {http://www.springerlink.com/index/djyncc1033h4vlpn.pdf http://www.cs.vu.nl/{~}annette/papers-pdf/2005AIMEMvG.pdf},\nyear = {2005}\n}\n
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\n \n \n\n \n \n \n \n Ontology-Driven Extraction of Linguistic Patterns for Modelling Clinical Guidelines.\n \n\n\n \n Serban, R.; Ten Teije, A.; Harmelen, F. V.; Marcos, M.; and Polo, C.\n \n\n\n \n\n\n\n In Miksch, S.; Hunter, J.; and Keravnou, E., editor(s), Proceedings of the 10th European Conference on Artificial Intelligence in Medicine (\\AIME\\-05), LNAI 3581, volume 3581, pages 191----200, 2005. Springer Verlag\n \n\n\n\n
\n\n\n \n \n \n \"Ontology-DrivenPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Serban2005,\nauthor = {Serban, Radu and {Ten Teije}, Annette and Harmelen, Frank Van and Marcos, Mar and Polo, Cristina},\nbooktitle = {Proceedings of the 10th European Conference on Artificial Intelligence in Medicine ({\\{}AIME{\\}}-05), LNAI 3581},\neditor = {Miksch, Silvia and Hunter, Jim and Keravnou, Elpida},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Serban et al. - 2005 - Ontology-Driven Extraction of Linguistic Patterns for Modelling Clinical Guidelines.pdf:pdf},\npages = {191----200},\npublisher = {Springer Verlag},\ntitle = {{Ontology-Driven Extraction of Linguistic Patterns for Modelling Clinical Guidelines}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2005AIMElinguistic.pdf},\nvolume = {3581},\nyear = {2005}\n}\n
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\n \n \n\n \n \n \n \n Design patterns for modelling medical guidelines.\n \n\n\n \n Serban, R.; Ten Teije, A.; Marcos, M.; Polo, C.; Rosenbrand, K.; Van Croonenborg, J.; and Wittenberg, J.\n \n\n\n \n\n\n\n In Miksch, S.; Hunter, J.; and Keravnou, E., editor(s), Proceedings of the 10th Conference on Artificial Intelligence in Medicine AIME 05(LNAI 3581), pages 121----125, 2005. Springer Verlag\n \n\n\n\n
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@inproceedings{Serban2005a,\nabstract = {It is by now widely accepted that medical guidelines and protocols can help to significantly improve the quality of medical care. Unfortunately, constructing the required medical guidelines is a very labour intensive and costly process. The cost of guideline construction would decrease if guidelines could be built from a set of building blocks that can be reused across guidelines. Such reusable building blocks would also result in more standardised guidelines, facilitating their deployment. The goal of this paper is to identify a collection of patterns that can be used as guideline building blocks.We propose two different methods for finding such patterns: either by observing regularities in the original text of the guidelines, or by first modelling the guideline in a formal language, and then observing regularities in the resulting formal models.We compare the collections of patterns obtained through these two methods, and experimentally validate some of the patterns by checking their usability in the actual modelling of a medical guideline for breastcancer treatment.},\nauthor = {Serban, Radu and {Ten Teije}, Annette and Marcos, Mar and Polo, Cristina and Rosenbrand, Kitty and {Van Croonenborg}, Joyce and Wittenberg, Jolanda},\nbooktitle = {Proceedings of the 10th Conference on Artificial Intelligence in Medicine AIME 05(LNAI 3581)},\neditor = {Miksch, Silvia and Hunter, Jim and Keravnou, Elpida},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Serban et al. - 2005 - Design patterns for modelling medical guidelines.pdf:pdf},\npages = {121----125},\npublisher = {Springer Verlag},\ntitle = {{Design patterns for modelling medical guidelines}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2005AIMElinguistic.pdf},\nyear = {2005}\n}\n
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\n It is by now widely accepted that medical guidelines and protocols can help to significantly improve the quality of medical care. Unfortunately, constructing the required medical guidelines is a very labour intensive and costly process. The cost of guideline construction would decrease if guidelines could be built from a set of building blocks that can be reused across guidelines. Such reusable building blocks would also result in more standardised guidelines, facilitating their deployment. The goal of this paper is to identify a collection of patterns that can be used as guideline building blocks.We propose two different methods for finding such patterns: either by observing regularities in the original text of the guidelines, or by first modelling the guideline in a formal language, and then observing regularities in the resulting formal models.We compare the collections of patterns obtained through these two methods, and experimentally validate some of the patterns by checking their usability in the actual modelling of a medical guideline for breastcancer treatment.\n
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\n \n \n\n \n \n \n \n Reasoning with Inconsistent Ontologies.\n \n\n\n \n Huang, Z.; Harmelen, F. V.; and Teije, A.\n \n\n\n \n\n\n\n In Proceedings of the Seventeenth Belgian/Dutch Conference on AI,(\\BNAIC\\'05), pages 1--2, Brussel, 2005. \n \n\n\n\n
\n\n\n \n \n \n \"ReasoningPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Huang2005,\naddress = {Brussel},\nauthor = {Huang, Zhisheng and Harmelen, Frank Van and Teije, Annette},\nbooktitle = {Proceedings of the Seventeenth Belgian/Dutch Conference on AI,({\\{}BNAIC{\\}}'05)},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Huang, Harmelen, Teije - 2005 - Reasoning with Inconsistent Ontologies.pdf:pdf},\nnumber = {i},\npages = {1--2},\ntitle = {{Reasoning with Inconsistent Ontologies}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2005BNAICZH.pdf},\nyear = {2005}\n}\n
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\n \n \n\n \n \n \n \n Web Service Composition for Deductive Web Mining : A Knowledge Modelling Approach.\n \n\n\n \n Svátek, V.; Ten Teije, A.; and Vacura, M.\n \n\n\n \n\n\n\n In Proceedings of Znalosti 2005, High Tatras, Slovak Republic, 2005. \n \n\n\n\n
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@inproceedings{Svatek2005,\naddress = {High Tatras, Slovak Republic},\nauthor = {Sv{\\'{a}}tek, Vojtech and {Ten Teije}, Annette and Vacura, Miroslav},\nbooktitle = {Proceedings of Znalosti 2005},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Sv{\\'{a}}tek, Ten Teije, Vacura - 2005 - Web Service Composition for Deductive Web Mining A Knowledge Modelling Approach.pdf:pdf},\ntitle = {{Web Service Composition for Deductive Web Mining : A Knowledge Modelling Approach}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2005ZNAL.pdf},\nyear = {2005}\n}\n
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\n \n \n\n \n \n \n \n Protocure: supporting the development of medical protocols through formal methods.\n \n\n\n \n Balser, M.; Coltell, O.; van Croonenborg, J.; Duelli, C.; van Harmelen, F.; Jovell, A.; Lucas, P.; Marcos, M.; Miksch, S.; Reif, W.; Rosenbrand, K.; Seyfang, A.; and ten Teije, A.\n \n\n\n \n\n\n\n In Proceedings of the Symposium of Computerised Protocols and Guidelines(\\SCPG\\-04), Studies in health technology and informatics, volume 101, pages 103--7, Praag, jan 2004. \n \n\n\n\n
\n\n\n \n \n \n \"Protocure:Paper\n  \n \n\n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Balser2004,\nabstract = {Medical guidelines and protocols describe the optimal care for a specific group of patients and therefore, when properly applied, improve the quality of patient care. During the last decade, a large number of medical guidelines and protocols have been published. However, the work done on developing and disseminating them far outweighs the efforts on guaranteeing their quality. Indeed, anomalies like ambiguity and incompleteness are frequent in medical guidelines and protocols. An approach grounded on a formal representation, can answer these needs, as we have demonstrated in the Protocure project'. The Protocure II project will aim at integrating formal methods in the life cycle of guidelines.},\naddress = {Praag},\nauthor = {Balser, Michael and Coltell, Oscar and van Croonenborg, Joyce and Duelli, Christoph and van Harmelen, Frank and Jovell, Albert and Lucas, Peter and Marcos, Mar and Miksch, Silvia and Reif, Wolfgang and Rosenbrand, Kitty and Seyfang, Andreas and ten Teije, Annette},\nbooktitle = {Proceedings of the Symposium of Computerised Protocols and Guidelines({\\{}SCPG{\\}}-04), Studies in health technology and informatics},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Balser et al. - 2004 - Protocure supporting the development of medical protocols through formal methods.pdf:pdf},\nissn = {0926-9630},\nkeywords = {Clinical Protocols,Decision Support Techniques,Evidence-Based Medicine,Humans,Planning Techniques,Practice Guidelines as Topic,Programming Languages,Software},\nmonth = {jan},\npages = {103--7},\npmid = {15537209},\ntitle = {{Protocure: supporting the development of medical protocols through formal methods.}},\nurl = {http://www.ncbi.nlm.nih.gov/pubmed/15537209 http://www.cs.vu.nl/{~}annette/papers-pdf/2004SCGP.pdf},\nvolume = {101},\nyear = {2004}\n}\n
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\n Medical guidelines and protocols describe the optimal care for a specific group of patients and therefore, when properly applied, improve the quality of patient care. During the last decade, a large number of medical guidelines and protocols have been published. However, the work done on developing and disseminating them far outweighs the efforts on guaranteeing their quality. Indeed, anomalies like ambiguity and incompleteness are frequent in medical guidelines and protocols. An approach grounded on a formal representation, can answer these needs, as we have demonstrated in the Protocure project'. The Protocure II project will aim at integrating formal methods in the life cycle of guidelines.\n
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\n \n \n\n \n \n \n \n Configuration of web services as parametric design.\n \n\n\n \n Ten Teije, A.; Van Harmelen, F.; and Wielinga, B.\n \n\n\n \n\n\n\n 2004.\n \n\n\n\n
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@misc{TenTeije2004,\naddress = {Valencia, Spain},\nauthor = {{Ten Teije}, Annette and {Van Harmelen}, Frank and Wielinga, Bob},\nbooktitle = {Engineering Knowledge in the Age of the SemanticWeb},\neditor = {{Lopez de Mantaras}, R. and Saitta, L.},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Ten Teije, Van Harmelen, Wielinga - 2004 - Configuration of web services as parametric design.pdf:pdf},\npages = {1097----1098},\npublisher = {IOS press},\ntitle = {{Configuration of web services as parametric design}},\nyear = {2004}\n}\n
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\n \n \n\n \n \n \n \n Towards a Structured Analysis of Approximate Problem Solving : a Case Study in Classification Approximate entailment.\n \n\n\n \n Groot, P.; Teije, A.; and Harmelen, F. V.\n \n\n\n \n\n\n\n In Dubois, D; Welty, C.; and Williams, M., editor(s), Proceedings of the Ninth International Conference on Principles of Knowledge Representation and Reasoning (\\KR'04\\), pages 399----406, Whistler, British Columbia, Canada, 2004. AAAI Press\n \n\n\n\n
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@inproceedings{Groot2004,\naddress = {Whistler, British Columbia, Canada},\nauthor = {Groot, Perry and Teije, Annette and Harmelen, Frank Van},\nbooktitle = {Proceedings of the Ninth International Conference on Principles of Knowledge Representation and Reasoning ({\\{}KR'04{\\}})},\neditor = {Dubois, D and Welty, C. and Williams, M.},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Groot, Teije, Harmelen - 2004 - Towards a Structured Analysis of Approximate Problem Solving a Case Study in Classification Approximate.pdf:pdf},\nkeywords = {anytime inference,approximate problem solving,classifica-,tion},\npages = {399----406},\npublisher = {AAAI Press},\ntitle = {{Towards a Structured Analysis of Approximate Problem Solving : a Case Study in Classification Approximate entailment}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2004KR.pdf},\nyear = {2004}\n}\n
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\n \n \n\n \n \n \n \n A quantitative analysis of the robustness of knowledge-based systems through degradation studies.\n \n\n\n \n Groot, P.; ten Teije, A.; and van Harmelen, F.\n \n\n\n \n\n\n\n Knowledge and Information Systems, 7(2): 224--245. apr 2004.\n \n\n\n\n
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@article{Groot2004a,\nauthor = {Groot, Perry and ten Teije, Annette and van Harmelen, Frank},\ndoi = {10.1007/s10115-003-0140-7},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Groot, ten Teije, van Harmelen - 2004 - A quantitative analysis of the robustness of knowledge-based systems through degradation studies.pdf:pdf},\nissn = {0219-1377},\njournal = {Knowledge and Information Systems},\nkeywords = {knowledge-based systems,quantitative analysis,robust behavior,validation},\nmonth = {apr},\nnumber = {2},\npages = {224--245},\ntitle = {{A quantitative analysis of the robustness of knowledge-based systems through degradation studies}},\nurl = {http://www.springerlink.com/index/10.1007/s10115-003-0140-7 http://www.cs.vu.nl/{~}annette/papers-pdf/2003KAIS.pdf},\nvolume = {7},\nyear = {2004}\n}\n
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\n \n \n\n \n \n \n \n Reaching diagnostic agreement in Multi-Agent Diagnosis.\n \n\n\n \n Roos, N.; TenTeije, A.; and Witteveen, C.\n \n\n\n \n\n\n\n In Jennings, N.; and Tambe, M., editor(s), Third International Joint Conference on Autonomous Agents and Multi-Agent Systems(\\AAMAS\\-2004), New York, 2004. ACM\n \n\n\n\n
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@inproceedings{Roos2004,\naddress = {New York},\nauthor = {Roos, Nico and TenTeije, Annette and Witteveen, Cees},\nbooktitle = {Third International Joint Conference on Autonomous Agents and Multi-Agent Systems({\\{}AAMAS{\\}}-2004)},\neditor = {Jennings, N. and Tambe, M.},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Roos, TenTeije, Witteveen - 2004 - Reaching diagnostic agreement in Multi-Agent Diagnosis.pdf:pdf},\npublisher = {ACM},\ntitle = {{Reaching diagnostic agreement in Multi-Agent Diagnosis}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2004AAMAS.pdf},\nyear = {2004}\n}\n
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\n \n \n\n \n \n \n \n Informal and formal medical guidelines: Bridging the gap.\n \n\n\n \n Geldof, M.; Ten Teije, A.; Van Harmelen, F.; Marcos, M.; and Votruba, P.\n \n\n\n \n\n\n\n In Artificial intelligence in medicine: 9th Conference on Artificial Intelligence in Medicine in Europe, AIME 2003, Protaras, Cyprus, October 18-22, 2003 proceedings, pages 173, 2003. Springer-Verlag New York Inc\n \n\n\n\n
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@inproceedings{Geldof2003,\nauthor = {Geldof, Marije and {Ten Teije}, A. and {Van Harmelen}, F. and Marcos, Mar and Votruba, P.},\nbooktitle = {Artificial intelligence in medicine: 9th Conference on Artificial Intelligence in Medicine in Europe, AIME 2003, Protaras, Cyprus, October 18-22, 2003 proceedings},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Geldof et al. - 2003 - Informal and formal medical guidelines Bridging the gap.pdf:pdf},\nisbn = {3540201297},\npages = {173},\npublisher = {Springer-Verlag New York Inc},\ntitle = {{Informal and formal medical guidelines: Bridging the gap}},\nurl = {http://books.google.com/books?hl=en{\\&}lr={\\&}id=3CNHhgwwlOoC{\\&}oi=fnd{\\&}pg=PA173{\\&}dq=Informal+and+formal+medical+guidelines+:+Bridging+the+gap{\\&}ots=DP4fRp{\\_}GNn{\\&}sig=w3Lue9s{\\_}Cn3RctvQ3cDhRkehGE0 http://www.cs.vu.nl/{~}annette/papers-pdf/2003AIM},\nyear = {2003}\n}\n
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\n \n \n\n \n \n \n \n Experiences in the Formalisation and Verification of Medical Protocols.\n \n\n\n \n Marcos, M.; Balser, M.; Ten Teije, A.; Van Harmelen, F.; and Duelli, C.\n \n\n\n \n\n\n\n In Artificial intelligence in medicine: 9th Conference on Artificial Intelligence in Medicine in Europe, AIME 2003, Protaras, Cyprus, October 18-22, 2003 proceedings, pages 132, 2003. Springer-Verlag New York Inc\n \n\n\n\n
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@inproceedings{Marcos2003,\nauthor = {Marcos, Mar and Balser, Michael and {Ten Teije}, Annette and {Van Harmelen}, Frank. and Duelli, Christoph},\nbooktitle = {Artificial intelligence in medicine: 9th Conference on Artificial Intelligence in Medicine in Europe, AIME 2003, Protaras, Cyprus, October 18-22, 2003 proceedings},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Marcos et al. - 2003 - Experiences in the Formalisation and Verification of Medical Protocols.pdf:pdf},\nisbn = {3540201297},\npages = {132},\npublisher = {Springer-Verlag New York Inc},\ntitle = {{Experiences in the Formalisation and Verification of Medical Protocols}},\nurl = {http://books.google.com/books?hl=en{\\&}lr={\\&}id=3CNHhgwwlOoC{\\&}oi=fnd{\\&}pg=PA132{\\&}dq=Experiences+in+the+formalisation+and+verification+of+medical+protocols{\\&}ots=DP4fRqRBLn{\\&}sig=-FXlZFvLS-Pr4fvmiearg0j9bxc http://www.cs.vu.nl/{~}annette/paper},\nyear = {2003}\n}\n
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\n \n \n\n \n \n \n \n A protocol for multi-agent diagnosis with spatially distributed knowledge.\n \n\n\n \n Roos, N.; Ten Teije, A.; and Witteveen, C.\n \n\n\n \n\n\n\n In Rosenschein, J.; and Wooldridge, M., editor(s), Proceedings of the second international joint conference on Autonomous agents and multiagent systems AAMAS 03, pages 655, 2003. ACM Press\n \n\n\n\n
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@inproceedings{Roos2003a,\nauthor = {Roos, Nico and {Ten Teije}, Annette and Witteveen, Cees},\nbooktitle = {Proceedings of the second international joint conference on Autonomous agents and multiagent systems AAMAS 03},\ndoi = {10.1145/860575.860681},\neditor = {Rosenschein, J. and Wooldridge, M.},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Roos, Ten Teije, Witteveen - 2003 - A protocol for multi-agent diagnosis with spatially distributed knowledge.pdf:pdf},\nisbn = {1581136838},\nkeywords = {model based diagnosis},\npages = {655},\npublisher = {ACM Press},\ntitle = {{A protocol for multi-agent diagnosis with spatially distributed knowledge}},\nurl = {http://portal.acm.org/citation.cfm?doid=860575.860681 http://www.cs.vu.nl/{~}annette/papers-pdf/2003AAMAS.pdf},\nyear = {2003}\n}\n
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\n \n \n\n \n \n \n \n Multi-Agent Diagnosis with semantically distributed knowledge.\n \n\n\n \n Roos, N.\n \n\n\n \n\n\n\n In Wiegerinck, W.; Vuurpijl, L.; Lucas, P.; and Heskes, T., editor(s), Proceedings of the 15th Belgium-Dutch Conference on Artificial Intelligence (\\BNAIC\\-2003), pages 259----266, Nijmegen, The Netherlands, 2003. \n \n\n\n\n
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@inproceedings{Roos2003,\naddress = {Nijmegen, The Netherlands},\nauthor = {Roos, Nico},\nbooktitle = {Proceedings of the 15th Belgium-Dutch Conference on Artificial Intelligence ({\\{}BNAIC{\\}}-2003)},\neditor = {Wiegerinck, W. and Vuurpijl, L. and Lucas, P. and Heskes, T.},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Roos - 2003 - Multi-Agent Diagnosis with semantically distributed knowledge.pdf:pdf},\npages = {259----266},\ntitle = {{Multi-Agent Diagnosis with semantically distributed knowledge}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2003BNAIC.pdf},\nyear = {2003}\n}\n
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\n \n \n\n \n \n \n \n Multi-Agent Diagnosis with spatially distributed knowledge.\n \n\n\n \n Roos, N.; Ten Teije, A.; Bos, A.; and Witteveen, C.\n \n\n\n \n\n\n\n In Blockeel, H.; and Denecker, M., editor(s), Proceedings of the 14th Belgium-Dutch Conference on Artificial Intelligence (\\BNAIC\\-2002), volume 2, Leuven, Belgium, 2002. \n \n\n\n\n
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@inproceedings{Roos2002,\naddress = {Leuven, Belgium},\nauthor = {Roos, Nico and {Ten Teije}, Annette and Bos, Andre and Witteveen, Cees},\nbooktitle = {Proceedings of the 14th Belgium-Dutch Conference on Artificial Intelligence ({\\{}BNAIC{\\}}-2002)},\neditor = {Blockeel, H. and Denecker, M.},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Roos et al. - 2002 - Multi-Agent Diagnosis with spatially distributed knowledge.pdf:pdf},\nnumber = {i},\ntitle = {{Multi-Agent Diagnosis with spatially distributed knowledge}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2002BNAIC.pdf},\nvolume = {2},\nyear = {2002}\n}\n
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\n \n \n\n \n \n \n \n Improving medical protocols through formalisation: a case study.\n \n\n\n \n Marcos, M.; Roomans, H.; ten Teije, A.; and Van Harmelen, F.\n \n\n\n \n\n\n\n In Proc. of the 6th Int. Conf. on Integrated Design and Process Technology (IDPT-02), California, 2002. \n \n\n\n\n
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@inproceedings{Marcos2002a,\naddress = {California},\nauthor = {Marcos, Mar and Roomans, Hugo and ten Teije, Annette and {Van Harmelen}, Frank},\nbooktitle = {Proc. of the 6th Int. Conf. on Integrated Design and Process Technology (IDPT-02)},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Marcos et al. - 2002 - Improving medical protocols through formalisation a case study.pdf:pdf},\ntitle = {{Improving medical protocols through formalisation: a case study}},\nurl = {http://www.math.vu.nl/{~}frankh/postscript/BNAIC02-prot.pdf http://www.cs.vu.nl/{~}annette/papers-pdf/2002IDPT.pdf},\nyear = {2002}\n}\n
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\n \n \n\n \n \n \n \n From informal knowledge to formal logic: a realistic case study in medical protocols.\n \n\n\n \n Marcos, M.; Balser, M.; Ten Teije, A.; and Van Harmelen, F.\n \n\n\n \n\n\n\n In Gomez-Perez, A.; and Benjamins, R., editor(s), Proceedings of the 12th European Workshop on Knowledge Acquisition, Modeling, and Management (\\EKAW\\-2002), LNAI, pages 3--13, Madrid, Spain, 2002. Springer\n \n\n\n\n
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@inproceedings{Marcos2002,\naddress = {Madrid, Spain},\nauthor = {Marcos, Mar and Balser, Michael and {Ten Teije}, Annette. and {Van Harmelen}, Frank.},\nbooktitle = {Proceedings of the 12th European Workshop on Knowledge Acquisition, Modeling, and Management ({\\{}EKAW{\\}}-2002), LNAI},\neditor = {Gomez-Perez, A. and Benjamins, R.},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Marcos et al. - 2002 - From informal knowledge to formal logic a realistic case study in medical protocols.pdf:pdf},\npages = {3--13},\npublisher = {Springer},\ntitle = {{From informal knowledge to formal logic: a realistic case study in medical protocols}},\nurl = {http://www.springerlink.com/index/P0PVCKUMW9N9FQ9U.pdf http://www.cs.vu.nl/{~}annette/papers-pdf/2002EKAW.pdf},\nyear = {2002}\n}\n
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\n \n \n\n \n \n \n \n Using critiquing for improving medical protocols: harder than it seems.\n \n\n\n \n Marcos, M.; Berger, G.; Van Harmelen, F.; ten Teije, A.; Roomans, H.; and Miksch, S.\n \n\n\n \n\n\n\n In Qualini, S.; Barahona, P.; and Andreassen, S., editor(s), Proceedings of the 8th European Conference on Artificial Intelligence in Medicine (\\AIME\\-01), LNAI 2101, pages 431--442, Dagstuhl, Germany, 2001. Springer\n \n\n\n\n
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@inproceedings{Marcos2001,\naddress = {Dagstuhl, Germany},\nauthor = {Marcos, Mar and Berger, Geert and {Van Harmelen}, Frank and ten Teije, Annette and Roomans, Hugo and Miksch, Silvia},\nbooktitle = {Proceedings of the 8th European Conference on Artificial Intelligence in Medicine ({\\{}AIME{\\}}-01), LNAI 2101},\neditor = {Qualini, S. and Barahona, P. and Andreassen, S.},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Marcos et al. - 2001 - Using critiquing for improving medical protocols harder than it seems.pdf:pdf},\npages = {431--442},\npublisher = {Springer},\ntitle = {{Using critiquing for improving medical protocols: harder than it seems}},\nurl = {http://www.springerlink.com/index/3lwhc660bnx77wvu.pdf http://www.cs.vu.nl/{~}annette/papers-pdf/2001AIME.pdf},\nyear = {2001}\n}\n
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\n \n \n\n \n \n \n \n Torture tests: a quantitative analysis for the robustness of knowledge-based systems.\n \n\n\n \n Groot, P; Van Harmelen, F; and Ten Teije, A\n \n\n\n \n\n\n\n In Proceedings of the European Workshop on Knowledge Acquisition Modelling and Management EKAW 00 LNAI SpringerVerlag, pages 403--418, 2000. \n \n\n\n\n
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@inproceedings{Groot2000,\nauthor = {Groot, P and {Van Harmelen}, F and {Ten Teije}, A},\nbooktitle = {Proceedings of the European Workshop on Knowledge Acquisition Modelling and Management EKAW 00 LNAI SpringerVerlag},\npages = {403--418},\ntitle = {{Torture tests: a quantitative analysis for the robustness of knowledge-based systems}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2000EKAW.pdf},\nyear = {2000}\n}\n
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\n \n \n\n \n \n \n \n Anytime diagnostic reasoning using approximate boolean constraint propagation.\n \n\n\n \n Verberne, A.; Van Harmelen, F.; and Ten Teije, A.\n \n\n\n \n\n\n\n In Proceedings of the Seventh International Conference on Principles of Knowledge Representation and Reasoning (\\KR'00\\), pages 323--332, Colorado, 2000. Citeseer\n \n\n\n\n
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@inproceedings{Verberne2000,\naddress = {Colorado},\nauthor = {Verberne, Alan and {Van Harmelen}, F. and {Ten Teije}, A.},\nbooktitle = {Proceedings of the Seventh International Conference on Principles of Knowledge Representation and Reasoning ({\\{}KR'00{\\}})},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Verberne, Van Harmelen, Ten Teije - 2000 - Anytime diagnostic reasoning using approximate boolean constraint propagation.pdf:pdf},\nkeywords = {deduction,diagnosis},\nnumber = {April},\npages = {323--332},\npublisher = {Citeseer},\ntitle = {{Anytime diagnostic reasoning using approximate boolean constraint propagation}},\nurl = {http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.34.3804{\\&}rep=rep1{\\&}type=pdf http://www.cs.vu.nl/{~}annette/papers-pdf/2000KR.pdf},\nyear = {2000}\n}\n
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\n \n \n\n \n \n \n \n Describing Problem Solving Methods using Anytime Performance Profiles.\n \n\n\n \n Ten Teije, A.; and Harmelen, F. V.\n \n\n\n \n\n\n\n In Proceedings of ECAI 2000, pages 78----82, 2000. \n \n\n\n\n
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@inproceedings{TenTeije2000,\nauthor = {{Ten Teije}, Annette and Harmelen, Frank Van},\nbooktitle = {Proceedings of ECAI 2000},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Ten Teije, Harmelen - 2000 - Describing Problem Solving Methods using Anytime Performance Profiles.pdf:pdf},\npages = {78----82},\ntitle = {{Describing Problem Solving Methods using Anytime Performance Profiles}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/2000ECAI.pdf},\nyear = {2000}\n}\n
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\n \n \n\n \n \n \n \n WP4 . 1 & 4 . 2 : Task & Method Adaptation.\n \n\n\n \n Teije, A.\n \n\n\n \n\n\n\n Technical Report 1999.\n \n\n\n\n
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@techreport{Teije1999,\nauthor = {Teije, Annette},\nbooktitle = {Medical Informatics},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Teije - 1999 - WP4 . 1 {\\&} 4 . 2 Task {\\&} Method Adaptation.pdf:pdf},\ntitle = {{WP4 . 1 {\\&} 4 . 2 : Task {\\&} Method Adaptation}},\nyear = {1999}\n}\n
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\n \n \n\n \n \n \n \n Describing Problem Solving Methods using Anytime Performance profiles.\n \n\n\n \n Ten Teije, A.; and Harmelen, F. V.\n \n\n\n \n\n\n\n In Benjamins, R., editor(s), Proceedings of the \\IJCAI\\'99 Workshop on Ontologies and Problem Solving Methods, pages 1--11, Stockholm, Sweden, 1999. \n \n\n\n\n
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@inproceedings{TenTeije1999,\naddress = {Stockholm, Sweden},\nauthor = {{Ten Teije}, Annette and Harmelen, Frank Van},\nbooktitle = {Proceedings of the {\\{}IJCAI{\\}}'99 Workshop on Ontologies and Problem Solving Methods},\neditor = {Benjamins, R.},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Ten Teije, Harmelen - 1999 - Describing Problem Solving Methods using Anytime Performance profiles.pdf:pdf},\npages = {1--11},\ntitle = {{Describing Problem Solving Methods using Anytime Performance profiles}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/1999IJCAIWS.pdf},\nyear = {1999}\n}\n
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\n \n \n\n \n \n \n \n Formally verifying dynamic properties of knowledge based systems.\n \n\n\n \n Groot, P.; ten Teije, A.; and Van Harmelen, F.\n \n\n\n \n\n\n\n In Fensel, D.; and Studer, R., editor(s), Proceedings 11th European Workshop on Knowledge Acquisition, Modeling, and Management (EKAW '99), LNAI 1621, pages 157--172, 1999. Springer\n \n\n\n\n
\n\n\n \n \n \n \"FormallyPaper\n  \n \n\n \n\n bibtex \n \n \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@inproceedings{Groot1999,\nauthor = {Groot, Perry and ten Teije, A. and {Van Harmelen}, F.},\nbooktitle = {Proceedings 11th European Workshop on Knowledge Acquisition, Modeling, and Management (EKAW '99), LNAI 1621},\neditor = {Fensel, D. and Studer, R.},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Groot, ten Teije, Van Harmelen - 1999 - Formally verifying dynamic properties of knowledge based systems.pdf:pdf},\npages = {157--172},\npublisher = {Springer},\ntitle = {{Formally verifying dynamic properties of knowledge based systems}},\nurl = {http://www.springerlink.com/index/FT55TXVEUPHFEBQK.pdf http://www.cs.vu.nl/{~}annette/papers-pdf/1999EKAW.pdf},\nyear = {1999}\n}\n
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\n \n \n\n \n \n \n \n A study of PROforma, a development methodology for clinical procedures.\n \n\n\n \n Vollebregt, A; Ten Teije, A; Van Harmelen, F; Van Der Lei, J; and Mosseveld, M\n \n\n\n \n\n\n\n Artificial Intelligence in Medicine, 17(2): 195--221. 1999.\n \n\n\n\n
\n\n\n \n \n \n \"APaper\n  \n \n\n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@article{Vollebregt1999,\nabstract = {Knowledge engineering has shown that besides the general methodologies from software engineering it is useful to develop special purpose methodologies for knowledge based systems (KBS). PROforma is a newly developed methodology for a specific type of knowledge based systems. PROforma is intended for decision support systems and in particular for clinical procedures in the medical domain. This paper reports on an evaluation study of PROforma, and on the trade-off that is involved between general purpose and special purpose development methods in Knowledge Engineering and Medical AI. Our method for evaluating PROforma is based on re-engineering a realistic system in two methodologies: the new and special purpose KBS methodology PROforma and the widely accepted, and more general KBS methodology CommonKADS. The four most important results from our study are as follows. Firstly, PROforma has some strong points which are also strong related to requirements of medical reasoning. Secondly, PROforma has some weak points, but none of them are in any way related to the special purpose nature of PROforma. Thirdly, a more general method like CommonKADS works better in the analysis phase than the more special purpose method PROforma. Finally, to support a complementary use of the methodologies, we propose a mapping between their respective languages.},\nauthor = {Vollebregt, A and {Ten Teije}, A and {Van Harmelen}, F and {Van Der Lei}, J and Mosseveld, M},\ninstitution = {Department of Computer Science and Mathematics, Vrije Universiteit Amsterdam, Boelelaan 1081a, 1081HV, Amsterdam, The Netherlands. A.M.Vollebregt@research.kpn.com},\njournal = {Artificial Intelligence in Medicine},\nnumber = {2},\npages = {195--221},\npmid = {10518051},\ntitle = {{A study of PROforma, a development methodology for clinical procedures.}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/1999AIIM.pdf},\nvolume = {17},\nyear = {1999}\n}\n
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\n Knowledge engineering has shown that besides the general methodologies from software engineering it is useful to develop special purpose methodologies for knowledge based systems (KBS). PROforma is a newly developed methodology for a specific type of knowledge based systems. PROforma is intended for decision support systems and in particular for clinical procedures in the medical domain. This paper reports on an evaluation study of PROforma, and on the trade-off that is involved between general purpose and special purpose development methods in Knowledge Engineering and Medical AI. Our method for evaluating PROforma is based on re-engineering a realistic system in two methodologies: the new and special purpose KBS methodology PROforma and the widely accepted, and more general KBS methodology CommonKADS. The four most important results from our study are as follows. Firstly, PROforma has some strong points which are also strong related to requirements of medical reasoning. Secondly, PROforma has some weak points, but none of them are in any way related to the special purpose nature of PROforma. Thirdly, a more general method like CommonKADS works better in the analysis phase than the more special purpose method PROforma. Finally, to support a complementary use of the methodologies, we propose a mapping between their respective languages.\n
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\n \n \n\n \n \n \n \n Construction of problem-solving methods as parametric design.\n \n\n\n \n Ten Teije, A; Van Harmelen, F; Schreiber, A T.; and Wielinga, B J\n \n\n\n \n\n\n\n Int J HumanComputer Studies, 49(4): 12.1----12.21. 1998.\n \n\n\n\n
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@article{TenTeije1998,\nauthor = {{Ten Teije}, A and {Van Harmelen}, F and Schreiber, A TH and Wielinga, B J},\njournal = {Int J HumanComputer Studies},\nnumber = {4},\npages = {12.1----12.21},\npublisher = {SRDG Publications, University of Calgary},\ntitle = {{Construction of problem-solving methods as parametric design}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/1998IJHCS.pdf},\nvolume = {49},\nyear = {1998}\n}\n
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\n \n \n\n \n \n \n \n Exploiting domain knowledge for approximate diagnosis.\n \n\n\n \n Ten Teije, A.; and Harmelen, F. V.\n \n\n\n \n\n\n\n In Pollack, M., editor(s), Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence (IJCAI97), volume 97, pages 454--459, Nagoya, Japan, 1997. Morgan Kaufman\n \n\n\n\n
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@inproceedings{TenTeije1997,\naddress = {Nagoya, Japan},\nauthor = {{Ten Teije}, Annette and Harmelen, Frank Van},\nbooktitle = {Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence (IJCAI97)},\neditor = {Pollack, M.},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Ten Teije, Harmelen - 1997 - Exploiting domain knowledge for approximate diagnosis.pdf:pdf},\npages = {454--459},\npublisher = {Morgan Kaufman},\ntitle = {{Exploiting domain knowledge for approximate diagnosis}},\nurl = {http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.43.7668{\\&}rep=rep1{\\&}type=pdf http://www.cs.vu.nl/{~}annette/papers-pdf/1997IJCAI.pdf},\nvolume = {97},\nyear = {1997}\n}\n
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\n \n \n\n \n \n \n \n Formalisation for decision support in anaesthesiology.\n \n\n\n \n Renardel De Lavalette, G R; Groenboom, R; Rotterdam, E; Van Harmelen, F; Ten Teije, A; and De Geus, F\n \n\n\n \n\n\n\n Artificial Intelligence in Medicine, 11(3): 189--214. 1997.\n \n\n\n\n
\n\n\n \n \n \n \"FormalisationPaper\n  \n \n\n \n\n bibtex \n \n \n \n  \n \n abstract \n \n\n \n\n \n\n \n \n \n \n \n \n \n \n\n\n
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@article{RenardelDeLavalette1997,\nabstract = {This paper reports on research for decision support for anaesthesiologists at the University Hospital in Groningen, the Netherlands. Based on CAROLA, an existing automated operation documentation system, we designed a support environment that will assist in real-time diagnosis. The core of the work presented here consists of a knowledge base (containing anaesthesiological knowledge) and a diagnosis system. The knowledge base is specified in the logic-based formal specification language AFSL. This leads to a powerful and precise treatment of knowledge structuring and data abstraction.},\nauthor = {{Renardel De Lavalette}, G R and Groenboom, R and Rotterdam, E and {Van Harmelen}, F and {Ten Teije}, A and {De Geus}, F},\ninstitution = {Department of Computing Science, University of Groningen, The Netherlands. grl@cs.rug.nl},\njournal = {Artificial Intelligence in Medicine},\nnumber = {3},\npages = {189--214},\npmid = {9413606},\npublisher = {Elsevier},\ntitle = {{Formalisation for decision support in anaesthesiology.}},\nurl = {http://linkinghub.elsevier.com/retrieve/pii/S0933365797000316 http://www.cs.vu.nl/{~}annette/papers-pdf/1997AIIM.pdf},\nvolume = {11},\nyear = {1997}\n}\n
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\n This paper reports on research for decision support for anaesthesiologists at the University Hospital in Groningen, the Netherlands. Based on CAROLA, an existing automated operation documentation system, we designed a support environment that will assist in real-time diagnosis. The core of the work presented here consists of a knowledge base (containing anaesthesiological knowledge) and a diagnosis system. The knowledge base is specified in the logic-based formal specification language AFSL. This leads to a powerful and precise treatment of knowledge structuring and data abstraction.\n
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\n \n \n\n \n \n \n \n Computing approximate diagnoses by using approximate entailment.\n \n\n\n \n Ten Teije, A.; and Harmelen, F. V.\n \n\n\n \n\n\n\n In Aiello, G.; and Doyle, J., editor(s), Proc. of the Fifth Int. Conference on Principles of Knowledge Representation and Reasoning (\\KR'96\\), 1996. Morgan Kaufman\n \n\n\n\n
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@inproceedings{TenTeije1996,\nauthor = {{Ten Teije}, Annette and Harmelen, Frank Van},\nbooktitle = {Proc. of the Fifth Int. Conference on Principles of Knowledge Representation and Reasoning ({\\{}KR'96{\\}})},\neditor = {Aiello, G. and Doyle, J.},\nfile = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Ten Teije, Harmelen - 1996 - Computing approximate diagnoses by using approximate entailment.pdf:pdf},\npublisher = {Morgan Kaufman},\ntitle = {{Computing approximate diagnoses by using approximate entailment}},\nurl = {http://www.cs.vu.nl/{~}annette/papers-pdf/1996KR.pdf},\nyear = {1996}\n}\n
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