var bibbase_data = {"data":"<img src=\"//bibbase.org/img/ajax-loader.gif\" id=\"spinner\"\n  style=\"display: none;\" alt=\"Loading..\" />\n\n<div id=\"bibbase\">\n\n  <script type=\"text/javascript\">\n    var bibbase = {\n      params: {\"jsonp\":\"1\",\"host\":\"bibbase.org\"},\n      data: [{\"title\":\"Modelling cheetah relocation success in southern Africa using an Iterative Bayesian Network Development Cycle\",\"type\":\"article\",\"year\":\"2010\",\"keywords\":\"Acinonyx jubatus,Bayesian network,Cheetah metapopulation,IBNDC,Iterative approach,Predator human conflict,Relocation\",\"pages\":\"641-651\",\"volume\":\"221\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0304380009007947\",\"month\":\"2\",\"id\":\"c05397ed-419b-34d5-b96a-cde7ecbe833c\",\"created\":\"2015-04-12T18:59:39.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"61ffc698-847a-3a7c-87f9-86532b1ed07b\",\"last_modified\":\"2017-03-14T14:39:09.523Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Relocation is one of the strategies used by conservationists to deal with problem cheetahs in southern Africa. The success of a relocation event and the factors that influence it within the broader context of long-term viability of wild cheetah metapopulations was the focus of a Bayesian Network (BN) modelling workshop in South Africa. Using a new heuristics, Iterative Bayesian Network Development Cycle (IBNDC), described in this paper, several networks were formulated to distinguish between the unique relocation experiences and conditions in Botswana and South Africa. There were many common underlying factors, despite the disparate relocation strategies and sites in the two countries. The benefit of relocation BNs goes beyond the identification and quantification of the factors influencing the success of relocations and population viability. They equip conservationists with a powerful communication tool in their negotiations with land and livestock owners, which is key to the long-term survival of cheetahs in southern Africa. Importantly, the IBNDC provides the ecological modeller with a methodological process that combines several BN design frameworks to facilitate the development of a BN in a multi-expert and multi-field domain.\",\"bibtype\":\"article\",\"author\":\"Johnson, Sandra and Mengersen, Kerrie and de Waal, Alta and Marnewick, Kelly and Cilliers, Deon and Houser, Ann Marie and Boast, Lorraine\",\"doi\":\"10.1016/j.ecolmodel.2009.11.012\",\"journal\":\"Ecological Modelling\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {Modelling cheetah relocation success in southern Africa using an Iterative Bayesian Network Development Cycle},\\n type = {article},\\n year = {2010},\\n keywords = {Acinonyx jubatus,Bayesian network,Cheetah metapopulation,IBNDC,Iterative approach,Predator human conflict,Relocation},\\n pages = {641-651},\\n volume = {221},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380009007947},\\n month = {2},\\n id = {c05397ed-419b-34d5-b96a-cde7ecbe833c},\\n created = {2015-04-12T18:59:39.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},\\n last_modified = {2017-03-14T14:39:09.523Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Relocation is one of the strategies used by conservationists to deal with problem cheetahs in southern Africa. The success of a relocation event and the factors that influence it within the broader context of long-term viability of wild cheetah metapopulations was the focus of a Bayesian Network (BN) modelling workshop in South Africa. Using a new heuristics, Iterative Bayesian Network Development Cycle (IBNDC), described in this paper, several networks were formulated to distinguish between the unique relocation experiences and conditions in Botswana and South Africa. There were many common underlying factors, despite the disparate relocation strategies and sites in the two countries. The benefit of relocation BNs goes beyond the identification and quantification of the factors influencing the success of relocations and population viability. They equip conservationists with a powerful communication tool in their negotiations with land and livestock owners, which is key to the long-term survival of cheetahs in southern Africa. Importantly, the IBNDC provides the ecological modeller with a methodological process that combines several BN design frameworks to facilitate the development of a BN in a multi-expert and multi-field domain.},\\n bibtype = {article},\\n author = {Johnson, Sandra and Mengersen, Kerrie and de Waal, Alta and Marnewick, Kelly and Cilliers, Deon and Houser, Ann Marie and Boast, Lorraine},\\n doi = {10.1016/j.ecolmodel.2009.11.012},\\n journal = {Ecological Modelling},\\n number = {4}\\n}\",\"author_short\":[\"Johnson,  S.\",\"Mengersen,  K.\",\"de Waal,  A.\",\"Marnewick,  K.\",\"Cilliers,  D.\",\"Houser,  A., M.\",\"Boast,  L.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0304380009007947\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"johnson-mengersen-dewaal-marnewick-cilliers-houser-boast-modellingcheetahrelocationsuccessinsouthernafricausinganiterativebayesiannetworkdevelopmentcycle-2010\",\"role\":\"author\",\"keyword\":[\"Acinonyx jubatus\",\"Bayesian network\",\"Cheetah metapopulation\",\"IBNDC\",\"Iterative approach\",\"Predator human conflict\",\"Relocation\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Not just data: a method for improving prediction with knowledge.\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Algorithms,Bayes Theorem,Blood Coagulation,Blood Coagulation Disorders,Blood Coagulation Disorders: therapy,Cluster Analysis,Decision Making,Decision Support Systems, Clinical,Diagnosis, Computer-Assisted,Emergency Medical Services,Emergency Medical Services: organization & adminis,Humans,Medical Errors,Medical Errors: prevention & control,Medical Informatics,Medical Informatics: methods,Medical Informatics: trends,Risk Assessment,Sensitivity and Specificity\",\"pages\":\"28-37\",\"volume\":\"48\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1532046413001640\",\"month\":\"4\",\"id\":\"a9159f5c-4a66-3b17-a9fb-7f0b441cf0f2\",\"created\":\"2015-04-12T20:17:35.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"61ffc698-847a-3a7c-87f9-86532b1ed07b\",\"last_modified\":\"2017-03-14T14:39:09.523Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Many medical conditions are only indirectly observed through symptoms and tests. Developing predictive models for such conditions is challenging since they can be thought of as 'latent' variables. They are not present in the data and often get confused with measurements. As a result, building a model that fits data well is not the same as making a prediction that is useful for decision makers. In this paper, we present a methodology for developing Bayesian network (BN) models that predict and reason with latent variables, using a combination of expert knowledge and available data. The method is illustrated by a case study into the prediction of acute traumatic coagulopathy (ATC), a disorder of blood clotting that significantly increases the risk of death following traumatic injuries. There are several measurements for ATC and previous models have predicted one of these measurements instead of the state of ATC itself. Our case study illustrates the advantages of models that distinguish between an underlying latent condition and its measurements, and of a continuing dialogue between the modeller and the domain experts as the model is developed using knowledge as well as data.\",\"bibtype\":\"article\",\"author\":\"Yet, Barbaros and Perkins, Zane and Fenton, Norman and Tai, Nigel and Marsh, William\",\"doi\":\"10.1016/j.jbi.2013.10.012\",\"journal\":\"Journal of biomedical informatics\",\"bibtex\":\"@article{\\n title = {Not just data: a method for improving prediction with knowledge.},\\n type = {article},\\n year = {2014},\\n keywords = {Algorithms,Bayes Theorem,Blood Coagulation,Blood Coagulation Disorders,Blood Coagulation Disorders: therapy,Cluster Analysis,Decision Making,Decision Support Systems, Clinical,Diagnosis, Computer-Assisted,Emergency Medical Services,Emergency Medical Services: organization & adminis,Humans,Medical Errors,Medical Errors: prevention & control,Medical Informatics,Medical Informatics: methods,Medical Informatics: trends,Risk Assessment,Sensitivity and Specificity},\\n pages = {28-37},\\n volume = {48},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1532046413001640},\\n month = {4},\\n id = {a9159f5c-4a66-3b17-a9fb-7f0b441cf0f2},\\n created = {2015-04-12T20:17:35.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},\\n last_modified = {2017-03-14T14:39:09.523Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Many medical conditions are only indirectly observed through symptoms and tests. Developing predictive models for such conditions is challenging since they can be thought of as 'latent' variables. They are not present in the data and often get confused with measurements. As a result, building a model that fits data well is not the same as making a prediction that is useful for decision makers. In this paper, we present a methodology for developing Bayesian network (BN) models that predict and reason with latent variables, using a combination of expert knowledge and available data. The method is illustrated by a case study into the prediction of acute traumatic coagulopathy (ATC), a disorder of blood clotting that significantly increases the risk of death following traumatic injuries. There are several measurements for ATC and previous models have predicted one of these measurements instead of the state of ATC itself. Our case study illustrates the advantages of models that distinguish between an underlying latent condition and its measurements, and of a continuing dialogue between the modeller and the domain experts as the model is developed using knowledge as well as data.},\\n bibtype = {article},\\n author = {Yet, Barbaros and Perkins, Zane and Fenton, Norman and Tai, Nigel and Marsh, William},\\n doi = {10.1016/j.jbi.2013.10.012},\\n journal = {Journal of biomedical informatics}\\n}\",\"author_short\":[\"Yet,  B.\",\"Perkins,  Z.\",\"Fenton,  N.\",\"Tai,  N.\",\"Marsh,  W.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1532046413001640\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"yet-perkins-fenton-tai-marsh-notjustdataamethodforimprovingpredictionwithknowledge-2014\",\"role\":\"author\",\"keyword\":[\"Algorithms\",\"Bayes Theorem\",\"Blood Coagulation\",\"Blood Coagulation Disorders\",\"Blood Coagulation Disorders: therapy\",\"Cluster Analysis\",\"Decision Making\",\"Decision Support Systems\",\"Clinical\",\"Diagnosis\",\"Computer-Assisted\",\"Emergency Medical Services\",\"Emergency Medical Services: organization & adminis\",\"Humans\",\"Medical Errors\",\"Medical Errors: prevention & control\",\"Medical Informatics\",\"Medical Informatics: methods\",\"Medical Informatics: trends\",\"Risk Assessment\",\"Sensitivity and Specificity\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":1,\"html\":\"\"},{\"title\":\"Common quandaries and their practical solutions in Bayesian network modeling\",\"type\":\"article\",\"year\":\"2017\",\"pages\":\"1-9\",\"volume\":\"358\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0304380016308134\",\"id\":\"6f3e525f-5e99-3f8e-8111-40cdae7203dc\",\"created\":\"2017-05-30T02:16:54.843Z\",\"accessed\":\"2017-05-29\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"61ffc698-847a-3a7c-87f9-86532b1ed07b\",\"last_modified\":\"2017-05-30T02:16:54.843Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Use and popularity of Bayesian network (BN) modeling has greatly expanded in recent years, but many common problems remain. Here, I summarize key problems in BN model construction and interpretation, along with suggested practical solutions. Problems in BN model construction include parameterizing probability values, variable definition, complex network structures, latent and confounding variables, outlier expert judgments, variable correlation, model peer review, tests of calibration and validation, model overfitting, and modeling wicked problems. Problems in BN model interpretation include objective creep, misconstruing variable influence, conflating correlation with causation, conflating proportion and expectation with probability, and using expert opinion. Solutions are offered for each problem and researchers are urged to innovate and share further solutions.\",\"bibtype\":\"article\",\"author\":\"Marcot, Bruce G.\",\"doi\":\"10.1016/j.ecolmodel.2017.05.011\",\"journal\":\"Ecological Modelling\",\"bibtex\":\"@article{\\n title = {Common quandaries and their practical solutions in Bayesian network modeling},\\n type = {article},\\n year = {2017},\\n pages = {1-9},\\n volume = {358},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380016308134},\\n id = {6f3e525f-5e99-3f8e-8111-40cdae7203dc},\\n created = {2017-05-30T02:16:54.843Z},\\n accessed = {2017-05-29},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},\\n last_modified = {2017-05-30T02:16:54.843Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Use and popularity of Bayesian network (BN) modeling has greatly expanded in recent years, but many common problems remain. Here, I summarize key problems in BN model construction and interpretation, along with suggested practical solutions. Problems in BN model construction include parameterizing probability values, variable definition, complex network structures, latent and confounding variables, outlier expert judgments, variable correlation, model peer review, tests of calibration and validation, model overfitting, and modeling wicked problems. Problems in BN model interpretation include objective creep, misconstruing variable influence, conflating correlation with causation, conflating proportion and expectation with probability, and using expert opinion. Solutions are offered for each problem and researchers are urged to innovate and share further solutions.},\\n bibtype = {article},\\n author = {Marcot, Bruce G.},\\n doi = {10.1016/j.ecolmodel.2017.05.011},\\n journal = {Ecological Modelling}\\n}\",\"author_short\":[\"Marcot,  B., G.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0304380016308134\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"marcot-commonquandariesandtheirpracticalsolutionsinbayesiannetworkmodeling-2017\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Methods for building Conditional Probability Tables of Bayesian Belief Networks from limited judgment: An evaluation for Human Reliability Application\",\"type\":\"article\",\"year\":\"2016\",\"pages\":\"93-112\",\"volume\":\"151\",\"websites\":\"http://linkinghub.elsevier.com/retrieve/pii/S0951832016000132\",\"month\":\"7\",\"publisher\":\"Elsevier Ltd\",\"id\":\"ea427921-cd23-3157-b5f0-ba00af919c18\",\"created\":\"2017-06-01T01:04:09.750Z\",\"accessed\":\"2017-05-31\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"61ffc698-847a-3a7c-87f9-86532b1ed07b\",\"last_modified\":\"2017-06-01T01:04:09.750Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Mkrtchyan, L. and Podofillini, L. and Dang, V.N.\",\"doi\":\"10.1016/j.ress.2016.01.004\",\"journal\":\"Reliability Engineering & System Safety\",\"bibtex\":\"@article{\\n title = {Methods for building Conditional Probability Tables of Bayesian Belief Networks from limited judgment: An evaluation for Human Reliability Application},\\n type = {article},\\n year = {2016},\\n pages = {93-112},\\n volume = {151},\\n websites = {http://linkinghub.elsevier.com/retrieve/pii/S0951832016000132},\\n month = {7},\\n publisher = {Elsevier Ltd},\\n id = {ea427921-cd23-3157-b5f0-ba00af919c18},\\n created = {2017-06-01T01:04:09.750Z},\\n accessed = {2017-05-31},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},\\n last_modified = {2017-06-01T01:04:09.750Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Mkrtchyan, L. and Podofillini, L. and Dang, V.N.},\\n doi = {10.1016/j.ress.2016.01.004},\\n journal = {Reliability Engineering & System Safety}\\n}\",\"author_short\":[\"Mkrtchyan,  L.\",\"Podofillini,  L.\",\"Dang,  V.\"],\"urls\":{\"Website\":\"http://linkinghub.elsevier.com/retrieve/pii/S0951832016000132\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"mkrtchyan-podofillini-dang-methodsforbuildingconditionalprobabilitytablesofbayesianbeliefnetworksfromlimitedjudgmentanevaluationforhumanreliabilityapplication-2016\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Modelling fatigue assessment at the vehicle driver’s station\",\"type\":\"article\",\"year\":\"2018\",\"pages\":\"02018\",\"volume\":\"10\",\"websites\":\"https://www.bio-conferences.org/10.1051/bioconf/20181002018\",\"month\":\"3\",\"publisher\":\"EDP Sciences\",\"day\":\"26\",\"id\":\"2f470d43-f230-3630-8f75-0f44f6b4eb7d\",\"created\":\"2018-03-31T21:30:03.124Z\",\"accessed\":\"2018-03-31\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"61ffc698-847a-3a7c-87f9-86532b1ed07b\",\"last_modified\":\"2018-03-31T21:30:03.124Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"The article presents the principles of fatigue assessment modeling in a driver's station using Bayesian networks. One of the causes of road collisions and accidents is fatigue. The factors determining fatigue are age of driver, psychophysical and health condition, time and length of the route being taken. At present, there is no clear criteria for assessing fatigue among professional drivers, so the objective of assessment is to attempt to design and construct a fatigue assessment model using Bayesian network technology.\",\"bibtype\":\"article\",\"author\":\"Maksym, Piotr and Pawlak, Halina\",\"editor\":\"Szeląg-Sikora, Anna\",\"doi\":\"10.1051/bioconf/20181002018\",\"journal\":\"BIO Web of Conferences\",\"bibtex\":\"@article{\\n title = {Modelling fatigue assessment at the vehicle driver’s station},\\n type = {article},\\n year = {2018},\\n pages = {02018},\\n volume = {10},\\n websites = {https://www.bio-conferences.org/10.1051/bioconf/20181002018},\\n month = {3},\\n publisher = {EDP Sciences},\\n day = {26},\\n id = {2f470d43-f230-3630-8f75-0f44f6b4eb7d},\\n created = {2018-03-31T21:30:03.124Z},\\n accessed = {2018-03-31},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},\\n last_modified = {2018-03-31T21:30:03.124Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The article presents the principles of fatigue assessment modeling in a driver's station using Bayesian networks. One of the causes of road collisions and accidents is fatigue. The factors determining fatigue are age of driver, psychophysical and health condition, time and length of the route being taken. At present, there is no clear criteria for assessing fatigue among professional drivers, so the objective of assessment is to attempt to design and construct a fatigue assessment model using Bayesian network technology.},\\n bibtype = {article},\\n author = {Maksym, Piotr and Pawlak, Halina},\\n editor = {Szeląg-Sikora, Anna},\\n doi = {10.1051/bioconf/20181002018},\\n journal = {BIO Web of Conferences}\\n}\",\"author_short\":[\"Maksym,  P.\",\"Pawlak,  H.\"],\"editor_short\":[\"Szeląg-Sikora,  A.\"],\"urls\":{\"Website\":\"https://www.bio-conferences.org/10.1051/bioconf/20181002018\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"maksym-pawlak-modellingfatigueassessmentatthevehicledriversstation-2018\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Modelling assessment of farmers workload\",\"type\":\"article\",\"year\":\"2018\",\"pages\":\"02026\",\"volume\":\"10\",\"websites\":\"https://www.bio-conferences.org/10.1051/bioconf/20181002026\",\"month\":\"3\",\"publisher\":\"EDP Sciences\",\"day\":\"26\",\"id\":\"fe1fe73d-f8b4-39b6-af28-9542f8c71e99\",\"created\":\"2018-03-31T21:34:10.083Z\",\"accessed\":\"2018-03-31\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"61ffc698-847a-3a7c-87f9-86532b1ed07b\",\"last_modified\":\"2018-03-31T21:34:10.083Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"The article presents the principles of modeling the physical load assessment of farmers using Bayesian Network technology. Despite rapid development of mechanization and automation of work processes in agriculture, many farmers use their own physical strength, such as manual handling of loads. There are periods in which a farmer performs several or even a dozen of variety activities during the 24 hours. It often happens that all these activities do in a hurry, without rest, working after several hours a day, which further strengthens his physical load. The variety of activities often causes problems with the use indicators to assess the physical load gauges, so Bayesian Network technology was used to develop the evaluation model.\",\"bibtype\":\"article\",\"author\":\"Pawlak, Halina and Maksym, Piotr\",\"editor\":\"Szeląg-Sikora, Anna\",\"doi\":\"10.1051/bioconf/20181002026\",\"journal\":\"BIO Web of Conferences\",\"bibtex\":\"@article{\\n title = {Modelling assessment of farmers workload},\\n type = {article},\\n year = {2018},\\n pages = {02026},\\n volume = {10},\\n websites = {https://www.bio-conferences.org/10.1051/bioconf/20181002026},\\n month = {3},\\n publisher = {EDP Sciences},\\n day = {26},\\n id = {fe1fe73d-f8b4-39b6-af28-9542f8c71e99},\\n created = {2018-03-31T21:34:10.083Z},\\n accessed = {2018-03-31},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},\\n last_modified = {2018-03-31T21:34:10.083Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The article presents the principles of modeling the physical load assessment of farmers using Bayesian Network technology. Despite rapid development of mechanization and automation of work processes in agriculture, many farmers use their own physical strength, such as manual handling of loads. There are periods in which a farmer performs several or even a dozen of variety activities during the 24 hours. It often happens that all these activities do in a hurry, without rest, working after several hours a day, which further strengthens his physical load. The variety of activities often causes problems with the use indicators to assess the physical load gauges, so Bayesian Network technology was used to develop the evaluation model.},\\n bibtype = {article},\\n author = {Pawlak, Halina and Maksym, Piotr},\\n editor = {Szeląg-Sikora, Anna},\\n doi = {10.1051/bioconf/20181002026},\\n journal = {BIO Web of Conferences}\\n}\",\"author_short\":[\"Pawlak,  H.\",\"Maksym,  P.\"],\"editor_short\":[\"Szeląg-Sikora,  A.\"],\"urls\":{\"Website\":\"https://www.bio-conferences.org/10.1051/bioconf/20181002026\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"pawlak-maksym-modellingassessmentoffarmersworkload-2018\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"On the Coherence of Probabilistic Relational Formalisms\",\"type\":\"article\",\"year\":\"2018\",\"keywords\":\"coherence checking,probabilistic relational models,relational Bayesian networks\",\"pages\":\"229\",\"volume\":\"20\",\"websites\":\"http://www.mdpi.com/1099-4300/20/4/229\",\"month\":\"3\",\"publisher\":\"Multidisciplinary Digital Publishing Institute\",\"day\":\"27\",\"id\":\"2f8b2524-c1ad-395e-afad-243e78dd63ef\",\"created\":\"2018-03-31T23:54:09.637Z\",\"accessed\":\"2018-03-31\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"61ffc698-847a-3a7c-87f9-86532b1ed07b\",\"last_modified\":\"2018-03-31T23:54:09.637Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"There are several formalisms that enhance Bayesian networks by including relations amongst individuals as modeling primitives. For instance, Probabilistic Relational Models (PRMs) use diagrams and relational databases to represent repetitive Bayesian networks, while Relational Bayesian Networks (RBNs) employ first-order probability formulas with the same purpose. We examine the coherence checking problem for those formalisms; that is, the problem of guaranteeing that any grounding of a well-formed set of sentences does produce a valid Bayesian network. This is a novel version of de Finetti’s problem of coherence checking for probabilistic assessments. We show how to reduce the coherence checking problem in relational Bayesian networks to a validity problem in first-order logic augmented with a transitive closure operator and how to combine this logic-based approach with faster, but incomplete algorithms.\",\"bibtype\":\"article\",\"author\":\"De Bona, Glauber and Cozman, Fabio\",\"doi\":\"10.3390/e20040229\",\"journal\":\"Entropy\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {On the Coherence of Probabilistic Relational Formalisms},\\n type = {article},\\n year = {2018},\\n keywords = {coherence checking,probabilistic relational models,relational Bayesian networks},\\n pages = {229},\\n volume = {20},\\n websites = {http://www.mdpi.com/1099-4300/20/4/229},\\n month = {3},\\n publisher = {Multidisciplinary Digital Publishing Institute},\\n day = {27},\\n id = {2f8b2524-c1ad-395e-afad-243e78dd63ef},\\n created = {2018-03-31T23:54:09.637Z},\\n accessed = {2018-03-31},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},\\n last_modified = {2018-03-31T23:54:09.637Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {There are several formalisms that enhance Bayesian networks by including relations amongst individuals as modeling primitives. For instance, Probabilistic Relational Models (PRMs) use diagrams and relational databases to represent repetitive Bayesian networks, while Relational Bayesian Networks (RBNs) employ first-order probability formulas with the same purpose. We examine the coherence checking problem for those formalisms; that is, the problem of guaranteeing that any grounding of a well-formed set of sentences does produce a valid Bayesian network. This is a novel version of de Finetti’s problem of coherence checking for probabilistic assessments. We show how to reduce the coherence checking problem in relational Bayesian networks to a validity problem in first-order logic augmented with a transitive closure operator and how to combine this logic-based approach with faster, but incomplete algorithms.},\\n bibtype = {article},\\n author = {De Bona, Glauber and Cozman, Fabio},\\n doi = {10.3390/e20040229},\\n journal = {Entropy},\\n number = {4}\\n}\",\"author_short\":[\"De Bona,  G.\",\"Cozman,  F.\"],\"urls\":{\"Website\":\"http://www.mdpi.com/1099-4300/20/4/229\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"debona-cozman-onthecoherenceofprobabilisticrelationalformalisms-2018\",\"role\":\"author\",\"keyword\":[\"coherence checking\",\"probabilistic relational models\",\"relational Bayesian networks\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Latent Variable Bayesian Networks Constructed Using Structural Equation Modelling\",\"type\":\"inproceedings\",\"year\":\"2018\",\"pages\":\"688-695\",\"websites\":\"https://ieeexplore.ieee.org/document/8455240/\",\"month\":\"7\",\"publisher\":\"IEEE\",\"city\":\"Cambridge, United Kingdom\",\"id\":\"0f7fe6a9-391e-3ff4-922d-fcef13ddb163\",\"created\":\"2018-09-18T12:20:19.813Z\",\"accessed\":\"2018-09-16\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"61ffc698-847a-3a7c-87f9-86532b1ed07b\",\"last_modified\":\"2018-09-18T12:20:19.813Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Bayesian networks in fusion systems often contain latent variables. They play an important role in fusion systems as they provide context which lead to better choices of data sources to fuse. Latent variables in Bayesian networks are mostly constructed by means of expert knowledge modelling. We propose using theory-driven structural equation modelling (SEM) to identify and structure latent variables in a Bayesian network. The linking of SEM and Bayesian networks is motivated by the fact that both methods can be shown to be causal models. We compare this approach to a data-driven approach where latent factors are induced by means of unsupervised learning. We identify appropriate metrics for URREF ontology criteria for both annroaches.\",\"bibtype\":\"inproceedings\",\"author\":\"de Waal, Alta and Yoo, Keunyoung\",\"doi\":\"10.23919/ICIF.2018.8455240\",\"booktitle\":\"2018 21st International Conference on Information Fusion (FUSION)\",\"bibtex\":\"@inproceedings{\\n title = {Latent Variable Bayesian Networks Constructed Using Structural Equation Modelling},\\n type = {inproceedings},\\n year = {2018},\\n pages = {688-695},\\n websites = {https://ieeexplore.ieee.org/document/8455240/},\\n month = {7},\\n publisher = {IEEE},\\n city = {Cambridge, United Kingdom},\\n id = {0f7fe6a9-391e-3ff4-922d-fcef13ddb163},\\n created = {2018-09-18T12:20:19.813Z},\\n accessed = {2018-09-16},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},\\n last_modified = {2018-09-18T12:20:19.813Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Bayesian networks in fusion systems often contain latent variables. They play an important role in fusion systems as they provide context which lead to better choices of data sources to fuse. Latent variables in Bayesian networks are mostly constructed by means of expert knowledge modelling. We propose using theory-driven structural equation modelling (SEM) to identify and structure latent variables in a Bayesian network. The linking of SEM and Bayesian networks is motivated by the fact that both methods can be shown to be causal models. We compare this approach to a data-driven approach where latent factors are induced by means of unsupervised learning. We identify appropriate metrics for URREF ontology criteria for both annroaches.},\\n bibtype = {inproceedings},\\n author = {de Waal, Alta and Yoo, Keunyoung},\\n doi = {10.23919/ICIF.2018.8455240},\\n booktitle = {2018 21st International Conference on Information Fusion (FUSION)}\\n}\",\"author_short\":[\"de Waal,  A.\",\"Yoo,  K.\"],\"urls\":{\"Website\":\"https://ieeexplore.ieee.org/document/8455240/\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"dewaal-yoo-latentvariablebayesiannetworksconstructedusingstructuralequationmodelling-2018\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Knowledge representation and diagnostic inference using Bayesian networks in the medical discourse\",\"type\":\"article\",\"year\":\"2019\",\"pages\":\"1-41\",\"websites\":\"http://arxiv.org/abs/1909.08549\",\"id\":\"6ae010b1-f27c-3700-8f6a-dec36f2dac7a\",\"created\":\"2019-09-24T16:30:02.872Z\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"61ffc698-847a-3a7c-87f9-86532b1ed07b\",\"last_modified\":\"2019-09-24T16:30:02.872Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"For the diagnostic inference under uncertainty Bayesian networks are investigated. The method is based on an adequate uniform representation of the necessary knowledge. This includes both generic and experience-based specific knowledge, which is stored in a knowledge base. For knowledge processing, a combination of the problem-solving methods of concept-based and case-based reasoning is used. Concept-based reasoning is used for the diagnosis, therapy and medication recommendation and evaluation of generic knowledge. Exceptions in the form of specific patient cases are processed by case-based reasoning. In addition, the use of Bayesian networks allows to deal with uncertainty, fuzziness and incompleteness. Thus, the valid general concepts can be issued according to their probability. To this end, various inference mechanisms are introduced and subsequently evaluated within the context of a developed prototype. Tests are employed to assess the classification of diagnoses by the network.\",\"bibtype\":\"article\",\"author\":\"Flügge, Sebastian and Zimmer, Sandra and Petersohn, Uwe\",\"bibtex\":\"@article{\\n title = {Knowledge representation and diagnostic inference using Bayesian networks in the medical discourse},\\n type = {article},\\n year = {2019},\\n pages = {1-41},\\n websites = {http://arxiv.org/abs/1909.08549},\\n id = {6ae010b1-f27c-3700-8f6a-dec36f2dac7a},\\n created = {2019-09-24T16:30:02.872Z},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},\\n last_modified = {2019-09-24T16:30:02.872Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {For the diagnostic inference under uncertainty Bayesian networks are investigated. The method is based on an adequate uniform representation of the necessary knowledge. This includes both generic and experience-based specific knowledge, which is stored in a knowledge base. For knowledge processing, a combination of the problem-solving methods of concept-based and case-based reasoning is used. Concept-based reasoning is used for the diagnosis, therapy and medication recommendation and evaluation of generic knowledge. Exceptions in the form of specific patient cases are processed by case-based reasoning. In addition, the use of Bayesian networks allows to deal with uncertainty, fuzziness and incompleteness. Thus, the valid general concepts can be issued according to their probability. To this end, various inference mechanisms are introduced and subsequently evaluated within the context of a developed prototype. Tests are employed to assess the classification of diagnoses by the network.},\\n bibtype = {article},\\n author = {Flügge, Sebastian and Zimmer, Sandra and Petersohn, Uwe}\\n}\",\"author_short\":[\"Flügge,  S.\",\"Zimmer,  S.\",\"Petersohn,  U.\"],\"urls\":{\"Website\":\"http://arxiv.org/abs/1909.08549\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"flgge-zimmer-petersohn-knowledgerepresentationanddiagnosticinferenceusingbayesiannetworksinthemedicaldiscourse-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"type\":\"inbook\",\"year\":\"2020\",\"pages\":\"347-370\",\"websites\":\"http://link.springer.com/10.1007/978-3-030-42553-1_14\",\"publisher\":\"Springer, Cham\",\"id\":\"814261f1-0ee6-3d25-8277-dcd26b47e8cd\",\"created\":\"2020-06-02T21:00:55.243Z\",\"accessed\":\"2020-06-02\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"61ffc698-847a-3a7c-87f9-86532b1ed07b\",\"last_modified\":\"2020-06-02T21:00:55.329Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"bibtype\":\"inbook\",\"author\":\"Davis, Jac and Good, Kyle and Hunter, Vanessa and Johnson, Sandra and Mengersen, Kerrie L.\",\"doi\":\"10.1007/978-3-030-42553-1_14\",\"chapter\":\"Bayesian Networks for Understanding Human-Wildlife Conflict in Conservation\",\"bibtex\":\"@inbook{\\n type = {inbook},\\n year = {2020},\\n pages = {347-370},\\n websites = {http://link.springer.com/10.1007/978-3-030-42553-1_14},\\n publisher = {Springer, Cham},\\n id = {814261f1-0ee6-3d25-8277-dcd26b47e8cd},\\n created = {2020-06-02T21:00:55.243Z},\\n accessed = {2020-06-02},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},\\n last_modified = {2020-06-02T21:00:55.329Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n bibtype = {inbook},\\n author = {Davis, Jac and Good, Kyle and Hunter, Vanessa and Johnson, Sandra and Mengersen, Kerrie L.},\\n doi = {10.1007/978-3-030-42553-1_14},\\n chapter = {Bayesian Networks for Understanding Human-Wildlife Conflict in Conservation}\\n}\",\"author_short\":[\"Davis,  J.\",\"Good,  K.\",\"Hunter,  V.\",\"Johnson,  S.\",\"Mengersen,  K., L.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/978-3-030-42553-1_14\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"davis-good-hunter-johnson-mengersen--2020\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"}],\n      metadata: {\"authorlinks\":{}},\n      ownerID: undefined\n    };\n  </script>\n\n  <script type=\"text/javascript\">\n  var site$;\n  if (typeof $ != 'undefined') {\n    console.log('existing jquery: storing and then restoring');\n    site$ = $;\n    $ = null;\n  }\n  </script>\n\n  <script src=\"https://ajax.googleapis.com/ajax/libs/jquery/2.2.4/jquery.min.js\">\n  </script>\n  <script type=\"text/javascript\">\n  if (site$) {\n    console.log('existing jquery: avoiding conflict and restoring');\n    bb$ = $.noConflict(true);\n    $ = site$;\n  } else {\n    bb$ = $;\n  }\n  </script>\n\n  <script src=\"//bibbase.org/js/bibbase.min.js\"\n          type=\"text/javascript\">\n  </script>\n\n  <script type=\"text/javascript\"\n          src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML\">\n  </script>\n  <script type=\"text/x-mathjax-config\">\n    MathJax.Hub.Config({tex2jax: {inlineMath: [['$','$'], ['\\\\(','\\\\)']]},\n                        skipTags: [\"body\"],\n                        processClass: \"bibbase_paper\"});\n  </script>\n\n  <style>\n  @media print {\n    .dontprint {\n        display: none !important;\n    }\n\n  .bibbase_group {\n    background-color: #E0E0E0;\n    font-style: italic;\n    font-size: larger;\n    text-shadow: 0px 0px 3px #FFFFFF;\n    border-radius: 4px 4px 4px 4px;\n    -moz-border-radius: 4px 4px 4px 4px;\n    -webkit-border-radius: 4px;\n    padding: 5px 40px 5px;\n    margin-top: 10px;\n    margin-bottom: 5px;\n    cursor: pointer;\n  }\n\n  .bibbase_paper {\n    margin-bottom: 5px;\n  }\n\n  }\n  </style>\n\n  \n  <div style=\"float: right; margin-right: 10px; margin-top: 10px; text-align: right; font-size: 12px\">\n    generated by\n    <a href=\"//bibbase.org\"\n       onclick=\"trackOutboundLink('bibbase', 'logo clicked', window.location.href, '//bibbase.org'); return false;\">\n      <img src=\"//bibbase.org/img/logo.svg\"\n           style=\"vertical-align: middle; margin-left: 3px; height: 16px;\"/\n           alt=\"bibbase.org\"\n           title=\"BibBase – The easiest way to maintain your publications page.\"\n        ></a>\n    \n  </div>\n  \n\n  <div id=\"bibbase_header\" class=\"dontprint\" style=\"\">\n\n    <ul class=\"nav nav-pills\" style=\"margin: 0px;\">\n\n      <li class=\"dropdown\" id=\"groupby_dropdown\">\n      <a class=\"dropdown-toggle\"\n         data-toggle=\"dropdown\"\n         href=\"#\">\n          Group by\n          <b class=\"caret\"></b>\n      </a>\n      <ul class=\"dropdown-menu\">\n        <li class=\"groupby year\"><a onclick=\"groupby('year')\">\n            Year</a>\n        </li>\n        <li class=\"groupby author\"><a onclick=\"groupby('author_short')\">\n            Author</a>\n        </li>\n        <li class=\"groupby type\"><a onclick=\"groupby('type')\">\n            Type</a>\n        </li>\n        <li class=\"groupby keyword\"><a onclick=\"groupby('keyword')\">\n            Keyword</a>\n        </li>\n        <li class=\"groupby downloads\"><a onclick=\"groupby('downloads')\">\n            Downloads</a>\n        </li>\n      </ul>\n      </li>\n\n\n      <li class=\"dropdown\" id=\"menu_dropdown\">\n      <a class=\"dropdown-toggle\"\n         data-toggle=\"dropdown\"\n         href=\"#\" alt=\"controls\">\n          <i class=\"fa fa-reorder\" alt=\"controls\"></i>\n          <b class=\"caret\"></b>\n      </a>\n      <ul class=\"dropdown-menu\">\n        <li>\n          <a onclick=\"toggleAll()\">\n            <i class=\"fa fa-chevron-down fa-fw\"></i> Expand/Collapse All\n          </a>\n        </li>\n        <li>\n          <a download=\"all.bib\" href=\"data:text/bibtex;base64,@article{
 title = {Modelling cheetah relocation success in southern Africa using an Iterative Bayesian Network Development Cycle},
 type = {article},
 year = {2010},
 keywords = {Acinonyx jubatus,Bayesian network,Cheetah metapopulation,IBNDC,Iterative approach,Predator human conflict,Relocation},
 pages = {641-651},
 volume = {221},
 websites = {http://www.sciencedirect.com/science/article/pii/S0304380009007947},
 month = {2},
 id = {c05397ed-419b-34d5-b96a-cde7ecbe833c},
 created = {2015-04-12T18:59:39.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},
 last_modified = {2017-03-14T14:39:09.523Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Relocation is one of the strategies used by conservationists to deal with problem cheetahs in southern Africa. The success of a relocation event and the factors that influence it within the broader context of long-term viability of wild cheetah metapopulations was the focus of a Bayesian Network (BN) modelling workshop in South Africa. Using a new heuristics, Iterative Bayesian Network Development Cycle (IBNDC), described in this paper, several networks were formulated to distinguish between the unique relocation experiences and conditions in Botswana and South Africa. There were many common underlying factors, despite the disparate relocation strategies and sites in the two countries. The benefit of relocation BNs goes beyond the identification and quantification of the factors influencing the success of relocations and population viability. They equip conservationists with a powerful communication tool in their negotiations with land and livestock owners, which is key to the long-term survival of cheetahs in southern Africa. Importantly, the IBNDC provides the ecological modeller with a methodological process that combines several BN design frameworks to facilitate the development of a BN in a multi-expert and multi-field domain.},
 bibtype = {article},
 author = {Johnson, Sandra and Mengersen, Kerrie and de Waal, Alta and Marnewick, Kelly and Cilliers, Deon and Houser, Ann Marie and Boast, Lorraine},
 doi = {10.1016/j.ecolmodel.2009.11.012},
 journal = {Ecological Modelling},
 number = {4}
}

@article{
 title = {Not just data: a method for improving prediction with knowledge.},
 type = {article},
 year = {2014},
 keywords = {Algorithms,Bayes Theorem,Blood Coagulation,Blood Coagulation Disorders,Blood Coagulation Disorders: therapy,Cluster Analysis,Decision Making,Decision Support Systems, Clinical,Diagnosis, Computer-Assisted,Emergency Medical Services,Emergency Medical Services: organization & adminis,Humans,Medical Errors,Medical Errors: prevention & control,Medical Informatics,Medical Informatics: methods,Medical Informatics: trends,Risk Assessment,Sensitivity and Specificity},
 pages = {28-37},
 volume = {48},
 websites = {http://www.sciencedirect.com/science/article/pii/S1532046413001640},
 month = {4},
 id = {a9159f5c-4a66-3b17-a9fb-7f0b441cf0f2},
 created = {2015-04-12T20:17:35.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},
 last_modified = {2017-03-14T14:39:09.523Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Many medical conditions are only indirectly observed through symptoms and tests. Developing predictive models for such conditions is challenging since they can be thought of as 'latent' variables. They are not present in the data and often get confused with measurements. As a result, building a model that fits data well is not the same as making a prediction that is useful for decision makers. In this paper, we present a methodology for developing Bayesian network (BN) models that predict and reason with latent variables, using a combination of expert knowledge and available data. The method is illustrated by a case study into the prediction of acute traumatic coagulopathy (ATC), a disorder of blood clotting that significantly increases the risk of death following traumatic injuries. There are several measurements for ATC and previous models have predicted one of these measurements instead of the state of ATC itself. Our case study illustrates the advantages of models that distinguish between an underlying latent condition and its measurements, and of a continuing dialogue between the modeller and the domain experts as the model is developed using knowledge as well as data.},
 bibtype = {article},
 author = {Yet, Barbaros and Perkins, Zane and Fenton, Norman and Tai, Nigel and Marsh, William},
 doi = {10.1016/j.jbi.2013.10.012},
 journal = {Journal of biomedical informatics}
}

@article{
 title = {Common quandaries and their practical solutions in Bayesian network modeling},
 type = {article},
 year = {2017},
 pages = {1-9},
 volume = {358},
 websites = {http://www.sciencedirect.com/science/article/pii/S0304380016308134},
 id = {6f3e525f-5e99-3f8e-8111-40cdae7203dc},
 created = {2017-05-30T02:16:54.843Z},
 accessed = {2017-05-29},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},
 last_modified = {2017-05-30T02:16:54.843Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Use and popularity of Bayesian network (BN) modeling has greatly expanded in recent years, but many common problems remain. Here, I summarize key problems in BN model construction and interpretation, along with suggested practical solutions. Problems in BN model construction include parameterizing probability values, variable definition, complex network structures, latent and confounding variables, outlier expert judgments, variable correlation, model peer review, tests of calibration and validation, model overfitting, and modeling wicked problems. Problems in BN model interpretation include objective creep, misconstruing variable influence, conflating correlation with causation, conflating proportion and expectation with probability, and using expert opinion. Solutions are offered for each problem and researchers are urged to innovate and share further solutions.},
 bibtype = {article},
 author = {Marcot, Bruce G.},
 doi = {10.1016/j.ecolmodel.2017.05.011},
 journal = {Ecological Modelling}
}

@article{
 title = {Methods for building Conditional Probability Tables of Bayesian Belief Networks from limited judgment: An evaluation for Human Reliability Application},
 type = {article},
 year = {2016},
 pages = {93-112},
 volume = {151},
 websites = {http://linkinghub.elsevier.com/retrieve/pii/S0951832016000132},
 month = {7},
 publisher = {Elsevier Ltd},
 id = {ea427921-cd23-3157-b5f0-ba00af919c18},
 created = {2017-06-01T01:04:09.750Z},
 accessed = {2017-05-31},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},
 last_modified = {2017-06-01T01:04:09.750Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 bibtype = {article},
 author = {Mkrtchyan, L. and Podofillini, L. and Dang, V.N.},
 doi = {10.1016/j.ress.2016.01.004},
 journal = {Reliability Engineering & System Safety}
}

@article{
 title = {Modelling fatigue assessment at the vehicle driver’s station},
 type = {article},
 year = {2018},
 pages = {02018},
 volume = {10},
 websites = {https://www.bio-conferences.org/10.1051/bioconf/20181002018},
 month = {3},
 publisher = {EDP Sciences},
 day = {26},
 id = {2f470d43-f230-3630-8f75-0f44f6b4eb7d},
 created = {2018-03-31T21:30:03.124Z},
 accessed = {2018-03-31},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},
 last_modified = {2018-03-31T21:30:03.124Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {The article presents the principles of fatigue assessment modeling in a driver's station using Bayesian networks. One of the causes of road collisions and accidents is fatigue. The factors determining fatigue are age of driver, psychophysical and health condition, time and length of the route being taken. At present, there is no clear criteria for assessing fatigue among professional drivers, so the objective of assessment is to attempt to design and construct a fatigue assessment model using Bayesian network technology.},
 bibtype = {article},
 author = {Maksym, Piotr and Pawlak, Halina},
 editor = {Szeląg-Sikora, Anna},
 doi = {10.1051/bioconf/20181002018},
 journal = {BIO Web of Conferences}
}

@article{
 title = {Modelling assessment of farmers workload},
 type = {article},
 year = {2018},
 pages = {02026},
 volume = {10},
 websites = {https://www.bio-conferences.org/10.1051/bioconf/20181002026},
 month = {3},
 publisher = {EDP Sciences},
 day = {26},
 id = {fe1fe73d-f8b4-39b6-af28-9542f8c71e99},
 created = {2018-03-31T21:34:10.083Z},
 accessed = {2018-03-31},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},
 last_modified = {2018-03-31T21:34:10.083Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The article presents the principles of modeling the physical load assessment of farmers using Bayesian Network technology. Despite rapid development of mechanization and automation of work processes in agriculture, many farmers use their own physical strength, such as manual handling of loads. There are periods in which a farmer performs several or even a dozen of variety activities during the 24 hours. It often happens that all these activities do in a hurry, without rest, working after several hours a day, which further strengthens his physical load. The variety of activities often causes problems with the use indicators to assess the physical load gauges, so Bayesian Network technology was used to develop the evaluation model.},
 bibtype = {article},
 author = {Pawlak, Halina and Maksym, Piotr},
 editor = {Szeląg-Sikora, Anna},
 doi = {10.1051/bioconf/20181002026},
 journal = {BIO Web of Conferences}
}

@article{
 title = {On the Coherence of Probabilistic Relational Formalisms},
 type = {article},
 year = {2018},
 keywords = {coherence checking,probabilistic relational models,relational Bayesian networks},
 pages = {229},
 volume = {20},
 websites = {http://www.mdpi.com/1099-4300/20/4/229},
 month = {3},
 publisher = {Multidisciplinary Digital Publishing Institute},
 day = {27},
 id = {2f8b2524-c1ad-395e-afad-243e78dd63ef},
 created = {2018-03-31T23:54:09.637Z},
 accessed = {2018-03-31},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},
 last_modified = {2018-03-31T23:54:09.637Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {There are several formalisms that enhance Bayesian networks by including relations amongst individuals as modeling primitives. For instance, Probabilistic Relational Models (PRMs) use diagrams and relational databases to represent repetitive Bayesian networks, while Relational Bayesian Networks (RBNs) employ first-order probability formulas with the same purpose. We examine the coherence checking problem for those formalisms; that is, the problem of guaranteeing that any grounding of a well-formed set of sentences does produce a valid Bayesian network. This is a novel version of de Finetti’s problem of coherence checking for probabilistic assessments. We show how to reduce the coherence checking problem in relational Bayesian networks to a validity problem in first-order logic augmented with a transitive closure operator and how to combine this logic-based approach with faster, but incomplete algorithms.},
 bibtype = {article},
 author = {De Bona, Glauber and Cozman, Fabio},
 doi = {10.3390/e20040229},
 journal = {Entropy},
 number = {4}
}

@inproceedings{
 title = {Latent Variable Bayesian Networks Constructed Using Structural Equation Modelling},
 type = {inproceedings},
 year = {2018},
 pages = {688-695},
 websites = {https://ieeexplore.ieee.org/document/8455240/},
 month = {7},
 publisher = {IEEE},
 city = {Cambridge, United Kingdom},
 id = {0f7fe6a9-391e-3ff4-922d-fcef13ddb163},
 created = {2018-09-18T12:20:19.813Z},
 accessed = {2018-09-16},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},
 last_modified = {2018-09-18T12:20:19.813Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Bayesian networks in fusion systems often contain latent variables. They play an important role in fusion systems as they provide context which lead to better choices of data sources to fuse. Latent variables in Bayesian networks are mostly constructed by means of expert knowledge modelling. We propose using theory-driven structural equation modelling (SEM) to identify and structure latent variables in a Bayesian network. The linking of SEM and Bayesian networks is motivated by the fact that both methods can be shown to be causal models. We compare this approach to a data-driven approach where latent factors are induced by means of unsupervised learning. We identify appropriate metrics for URREF ontology criteria for both annroaches.},
 bibtype = {inproceedings},
 author = {de Waal, Alta and Yoo, Keunyoung},
 doi = {10.23919/ICIF.2018.8455240},
 booktitle = {2018 21st International Conference on Information Fusion (FUSION)}
}

@article{
 title = {Knowledge representation and diagnostic inference using Bayesian networks in the medical discourse},
 type = {article},
 year = {2019},
 pages = {1-41},
 websites = {http://arxiv.org/abs/1909.08549},
 id = {6ae010b1-f27c-3700-8f6a-dec36f2dac7a},
 created = {2019-09-24T16:30:02.872Z},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},
 last_modified = {2019-09-24T16:30:02.872Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {For the diagnostic inference under uncertainty Bayesian networks are investigated. The method is based on an adequate uniform representation of the necessary knowledge. This includes both generic and experience-based specific knowledge, which is stored in a knowledge base. For knowledge processing, a combination of the problem-solving methods of concept-based and case-based reasoning is used. Concept-based reasoning is used for the diagnosis, therapy and medication recommendation and evaluation of generic knowledge. Exceptions in the form of specific patient cases are processed by case-based reasoning. In addition, the use of Bayesian networks allows to deal with uncertainty, fuzziness and incompleteness. Thus, the valid general concepts can be issued according to their probability. To this end, various inference mechanisms are introduced and subsequently evaluated within the context of a developed prototype. Tests are employed to assess the classification of diagnoses by the network.},
 bibtype = {article},
 author = {Flügge, Sebastian and Zimmer, Sandra and Petersohn, Uwe}
}

@inbook{
 type = {inbook},
 year = {2020},
 pages = {347-370},
 websites = {http://link.springer.com/10.1007/978-3-030-42553-1_14},
 publisher = {Springer, Cham},
 id = {814261f1-0ee6-3d25-8277-dcd26b47e8cd},
 created = {2020-06-02T21:00:55.243Z},
 accessed = {2020-06-02},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},
 last_modified = {2020-06-02T21:00:55.329Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 bibtype = {inbook},
 author = {Davis, Jac and Good, Kyle and Hunter, Vanessa and Johnson, Sandra and Mengersen, Kerrie L.},
 doi = {10.1007/978-3-030-42553-1_14},
 chapter = {Bayesian Networks for Understanding Human-Wildlife Conflict in Conservation}
}\">\n            <i class=\"fa fa-download fa-fw\"></i> Download BibTeX\n          </a>\n        </li>\n        <li>\n          <a href=\"//bibbase.org/rss?bib=\">\n            <i class=\"fa fa-rss fa-fw\"></i> RSS Feed\n          </a>\n          </li>\n      </ul>\n      </li>\n\n      \n\n\n      \n    </ul>\n\n\n    <div class=\"alert alert-success bibbase_msg\" id=\"bibbase_msg_embed\"\n         style=\"display: none;\">\n\n      Excellent! Next you can\n      <a href=\"/network/register?next=/network/newSiteFromTemplate%3Fbiburl=\"\n      >create a new website with this list</a>, or\n      embed it in an existing web page by copying &amp; pasting\n      any of the following snippets.\n\n      <div style=\"text-align: left; margin-top: 1em;\">\n        <strong>JavaScript</strong>\n        <span class=\"comment recommended\">(easiest)</span>\n        <div class=\"well well-small\">\n          <code>\n            &lt;script src=\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0/group/61ffc698-847a-3a7c-87f9-86532b1ed07b?jsonp=1&amp;jsonp=1\"&gt;&lt;/script&gt;\n          </code>\n        </div>\n\n        <strong>PHP</strong>\n        <div class=\"well well-small\">\n          <code>\n            &lt;?php\n            $contents = file_get_contents(\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0/group/61ffc698-847a-3a7c-87f9-86532b1ed07b?jsonp=1\");\n            print_r($contents);\n            ?&gt;\n          </code>\n        </div>\n\n        <strong>iFrame</strong>\n        <span class=\"comment\">(not recommended)</span>\n        <div class=\"well well-small\">\n          <code>\n            &lt;iframe src=\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0/group/61ffc698-847a-3a7c-87f9-86532b1ed07b?jsonp=1\"&gt;&lt;/iframe&gt;\n          </code>\n        </div>\n\n        <p>\n          For more details see the <a href=\"//bibbase.org/help\">documention</a>.\n        </p>\n      </div>\n    </div>\n\n    <div class=\"alert alert-success bibbase_msg\" id=\"bibbase_msg_preview\"\n         style=\"display: none;\">\n\n      This is a preview! To use this list on your own web site\n      or create a new web site from it,\n      <a href=\"/network/register?next=/network/newAccountWithFile%3FfileId=\"\n      >create a free account</a>. The file will be added\n      and you will be able to edit it in the File Manager.\n      We will show you instructions once you've created your account.\n    </div>\n\n    <div class=\"alert alert-warning bibbase_msg\" id=\"bibbase_msg_mendeley1\"\n         style=\"display: none;\">\n\n      <p>To the site owner:</p>\n\n      <p><strong>Action required!</strong> Mendeley is changing its\n        API. In order to keep using Mendeley with BibBase past April\n        14th, you need to:\n        <ol>\n          <li>renew the authorization for BibBase on Mendeley, and</li>\n          <li>update the BibBase URL\n            in your page the same way you did when you initially set up\n            this page.\n          </li>\n        </ol>\n      </p>\n\n      <p>\n        <a href=\"http://bibbase.org/cgi-bin/mendeley2/get.py\">\n          <i class=\"fa fa-angle-double-right\"></i>\n          Fix it now</a>\n      </p>\n    </div>\n\n  </div>\n\n\n  <div id=\"bibbase_body\">\n    \n  \n  <div class=\"bibbase_group_whole\" id=\"group_2020\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2020')\"\n      onkeypress=\"toggleGroup('group_2020')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2020</span>\n      <span class=\"bibbase_group_count\">\n        \n        (1)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"davis-good-hunter-johnson-mengersen--2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/978-3-030-42553-1_14\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'davis-good-hunter-johnson-mengersen--2020', 'http://link.springer.com/10.1007/978-3-030-42553-1_14', event);\">\n    Bayesian Networks for Understanding Human-Wildlife Conflict in Conservation.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Davis,  J.; Good,  K.; Hunter,  V.; Johnson,  S.;  and Mengersen,  K., L.\n</span>\n\n  \n\n</span>\n\n  pages 347-370. Springer, Cham,  2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/978-3-030-42553-1_14\"\n     onclick=\"log_download('davis-good-hunter-johnson-mengersen--2020', 'http://link.springer.com/10.1007/978-3-030-42553-1_14', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\" [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/978-3-030-42553-1_14\"\n     onclick=\"log_download('davis-good-hunter-johnson-mengersen--2020', 'http://doi.org/10.1007/978-3-030-42553-1_14', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/davis-good-hunter-johnson-mengersen--2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('davis-good-hunter-johnson-mengersen--2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inbook{\n type = {inbook},\n year = {2020},\n pages = {347-370},\n websites = {http://link.springer.com/10.1007/978-3-030-42553-1_14},\n publisher = {Springer, Cham},\n id = {814261f1-0ee6-3d25-8277-dcd26b47e8cd},\n created = {2020-06-02T21:00:55.243Z},\n accessed = {2020-06-02},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},\n last_modified = {2020-06-02T21:00:55.329Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n bibtype = {inbook},\n author = {Davis, Jac and Good, Kyle and Hunter, Vanessa and Johnson, Sandra and Mengersen, Kerrie L.},\n doi = {10.1007/978-3-030-42553-1_14},\n chapter = {Bayesian Networks for Understanding Human-Wildlife Conflict in Conservation}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2019\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2019')\"\n      onkeypress=\"toggleGroup('group_2019')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2019</span>\n      <span class=\"bibbase_group_count\">\n        \n        (1)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"flgge-zimmer-petersohn-knowledgerepresentationanddiagnosticinferenceusingbayesiannetworksinthemedicaldiscourse-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://arxiv.org/abs/1909.08549\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'flgge-zimmer-petersohn-knowledgerepresentationanddiagnosticinferenceusingbayesiannetworksinthemedicaldiscourse-2019', 'http://arxiv.org/abs/1909.08549', event);\">\n    Knowledge representation and diagnostic inference using Bayesian networks in the medical discourse.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Flügge,  S.; Zimmer,  S.;  and Petersohn,  U.\n</span>\n\n  \n\n</span>\n\n  ,1-41.  2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://arxiv.org/abs/1909.08549\"\n     onclick=\"log_download('flgge-zimmer-petersohn-knowledgerepresentationanddiagnosticinferenceusingbayesiannetworksinthemedicaldiscourse-2019', 'http://arxiv.org/abs/1909.08549', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Knowledge representation and diagnostic inference using Bayesian networks in the medical discourse [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/flgge-zimmer-petersohn-knowledgerepresentationanddiagnosticinferenceusingbayesiannetworksinthemedicaldiscourse-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('flgge-zimmer-petersohn-knowledgerepresentationanddiagnosticinferenceusingbayesiannetworksinthemedicaldiscourse-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Knowledge representation and diagnostic inference using Bayesian networks in the medical discourse},\n type = {article},\n year = {2019},\n pages = {1-41},\n websites = {http://arxiv.org/abs/1909.08549},\n id = {6ae010b1-f27c-3700-8f6a-dec36f2dac7a},\n created = {2019-09-24T16:30:02.872Z},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},\n last_modified = {2019-09-24T16:30:02.872Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {For the diagnostic inference under uncertainty Bayesian networks are investigated. The method is based on an adequate uniform representation of the necessary knowledge. This includes both generic and experience-based specific knowledge, which is stored in a knowledge base. For knowledge processing, a combination of the problem-solving methods of concept-based and case-based reasoning is used. Concept-based reasoning is used for the diagnosis, therapy and medication recommendation and evaluation of generic knowledge. Exceptions in the form of specific patient cases are processed by case-based reasoning. In addition, the use of Bayesian networks allows to deal with uncertainty, fuzziness and incompleteness. Thus, the valid general concepts can be issued according to their probability. To this end, various inference mechanisms are introduced and subsequently evaluated within the context of a developed prototype. Tests are employed to assess the classification of diagnoses by the network.},\n bibtype = {article},\n author = {Flügge, Sebastian and Zimmer, Sandra and Petersohn, Uwe}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  For the diagnostic inference under uncertainty Bayesian networks are investigated. The method is based on an adequate uniform representation of the necessary knowledge. This includes both generic and experience-based specific knowledge, which is stored in a knowledge base. For knowledge processing, a combination of the problem-solving methods of concept-based and case-based reasoning is used. Concept-based reasoning is used for the diagnosis, therapy and medication recommendation and evaluation of generic knowledge. Exceptions in the form of specific patient cases are processed by case-based reasoning. In addition, the use of Bayesian networks allows to deal with uncertainty, fuzziness and incompleteness. Thus, the valid general concepts can be issued according to their probability. To this end, various inference mechanisms are introduced and subsequently evaluated within the context of a developed prototype. Tests are employed to assess the classification of diagnoses by the network.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2018\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2018')\"\n      onkeypress=\"toggleGroup('group_2018')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2018</span>\n      <span class=\"bibbase_group_count\">\n        \n        (4)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"maksym-pawlak-modellingfatigueassessmentatthevehicledriversstation-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.bio-conferences.org/10.1051/bioconf/20181002018\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'maksym-pawlak-modellingfatigueassessmentatthevehicledriversstation-2018', 'https://www.bio-conferences.org/10.1051/bioconf/20181002018', event);\">\n    Modelling fatigue assessment at the vehicle driver’s station.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Maksym,  P.;  and Pawlak,  H.\n</span>\n\n  \n\n</span>\n\n  <i>BIO Web of Conferences</i>, 10: 02018. 3 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.bio-conferences.org/10.1051/bioconf/20181002018\"\n     onclick=\"log_download('maksym-pawlak-modellingfatigueassessmentatthevehicledriversstation-2018', 'https://www.bio-conferences.org/10.1051/bioconf/20181002018', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Modelling fatigue assessment at the vehicle driver’s station [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1051/bioconf/20181002018\"\n     onclick=\"log_download('maksym-pawlak-modellingfatigueassessmentatthevehicledriversstation-2018', 'http://doi.org/10.1051/bioconf/20181002018', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/maksym-pawlak-modellingfatigueassessmentatthevehicledriversstation-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('maksym-pawlak-modellingfatigueassessmentatthevehicledriversstation-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Modelling fatigue assessment at the vehicle driver’s station},\n type = {article},\n year = {2018},\n pages = {02018},\n volume = {10},\n websites = {https://www.bio-conferences.org/10.1051/bioconf/20181002018},\n month = {3},\n publisher = {EDP Sciences},\n day = {26},\n id = {2f470d43-f230-3630-8f75-0f44f6b4eb7d},\n created = {2018-03-31T21:30:03.124Z},\n accessed = {2018-03-31},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},\n last_modified = {2018-03-31T21:30:03.124Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {The article presents the principles of fatigue assessment modeling in a driver&#x27;s station using Bayesian networks. One of the causes of road collisions and accidents is fatigue. The factors determining fatigue are age of driver, psychophysical and health condition, time and length of the route being taken. At present, there is no clear criteria for assessing fatigue among professional drivers, so the objective of assessment is to attempt to design and construct a fatigue assessment model using Bayesian network technology.},\n bibtype = {article},\n author = {Maksym, Piotr and Pawlak, Halina},\n editor = {Szeląg-Sikora, Anna},\n doi = {10.1051/bioconf/20181002018},\n journal = {BIO Web of Conferences}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The article presents the principles of fatigue assessment modeling in a driver's station using Bayesian networks. One of the causes of road collisions and accidents is fatigue. The factors determining fatigue are age of driver, psychophysical and health condition, time and length of the route being taken. At present, there is no clear criteria for assessing fatigue among professional drivers, so the objective of assessment is to attempt to design and construct a fatigue assessment model using Bayesian network technology.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"pawlak-maksym-modellingassessmentoffarmersworkload-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.bio-conferences.org/10.1051/bioconf/20181002026\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'pawlak-maksym-modellingassessmentoffarmersworkload-2018', 'https://www.bio-conferences.org/10.1051/bioconf/20181002026', event);\">\n    Modelling assessment of farmers workload.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Pawlak,  H.;  and Maksym,  P.\n</span>\n\n  \n\n</span>\n\n  <i>BIO Web of Conferences</i>, 10: 02026. 3 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.bio-conferences.org/10.1051/bioconf/20181002026\"\n     onclick=\"log_download('pawlak-maksym-modellingassessmentoffarmersworkload-2018', 'https://www.bio-conferences.org/10.1051/bioconf/20181002026', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Modelling assessment of farmers workload [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1051/bioconf/20181002026\"\n     onclick=\"log_download('pawlak-maksym-modellingassessmentoffarmersworkload-2018', 'http://doi.org/10.1051/bioconf/20181002026', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/pawlak-maksym-modellingassessmentoffarmersworkload-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('pawlak-maksym-modellingassessmentoffarmersworkload-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Modelling assessment of farmers workload},\n type = {article},\n year = {2018},\n pages = {02026},\n volume = {10},\n websites = {https://www.bio-conferences.org/10.1051/bioconf/20181002026},\n month = {3},\n publisher = {EDP Sciences},\n day = {26},\n id = {fe1fe73d-f8b4-39b6-af28-9542f8c71e99},\n created = {2018-03-31T21:34:10.083Z},\n accessed = {2018-03-31},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},\n last_modified = {2018-03-31T21:34:10.083Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The article presents the principles of modeling the physical load assessment of farmers using Bayesian Network technology. Despite rapid development of mechanization and automation of work processes in agriculture, many farmers use their own physical strength, such as manual handling of loads. There are periods in which a farmer performs several or even a dozen of variety activities during the 24 hours. It often happens that all these activities do in a hurry, without rest, working after several hours a day, which further strengthens his physical load. The variety of activities often causes problems with the use indicators to assess the physical load gauges, so Bayesian Network technology was used to develop the evaluation model.},\n bibtype = {article},\n author = {Pawlak, Halina and Maksym, Piotr},\n editor = {Szeląg-Sikora, Anna},\n doi = {10.1051/bioconf/20181002026},\n journal = {BIO Web of Conferences}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The article presents the principles of modeling the physical load assessment of farmers using Bayesian Network technology. Despite rapid development of mechanization and automation of work processes in agriculture, many farmers use their own physical strength, such as manual handling of loads. There are periods in which a farmer performs several or even a dozen of variety activities during the 24 hours. It often happens that all these activities do in a hurry, without rest, working after several hours a day, which further strengthens his physical load. The variety of activities often causes problems with the use indicators to assess the physical load gauges, so Bayesian Network technology was used to develop the evaluation model.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"debona-cozman-onthecoherenceofprobabilisticrelationalformalisms-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.mdpi.com/1099-4300/20/4/229\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'debona-cozman-onthecoherenceofprobabilisticrelationalformalisms-2018', 'http://www.mdpi.com/1099-4300/20/4/229', event);\">\n    On the Coherence of Probabilistic Relational Formalisms.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  De Bona,  G.;  and Cozman,  F.\n</span>\n\n  \n\n</span>\n\n  <i>Entropy</i>, 20(4): 229. 3 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.mdpi.com/1099-4300/20/4/229\"\n     onclick=\"log_download('debona-cozman-onthecoherenceofprobabilisticrelationalformalisms-2018', 'http://www.mdpi.com/1099-4300/20/4/229', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"On the Coherence of Probabilistic Relational Formalisms [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.3390/e20040229\"\n     onclick=\"log_download('debona-cozman-onthecoherenceofprobabilisticrelationalformalisms-2018', 'http://doi.org/10.3390/e20040229', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/debona-cozman-onthecoherenceofprobabilisticrelationalformalisms-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('debona-cozman-onthecoherenceofprobabilisticrelationalformalisms-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {On the Coherence of Probabilistic Relational Formalisms},\n type = {article},\n year = {2018},\n keywords = {coherence checking,probabilistic relational models,relational Bayesian networks},\n pages = {229},\n volume = {20},\n websites = {http://www.mdpi.com/1099-4300/20/4/229},\n month = {3},\n publisher = {Multidisciplinary Digital Publishing Institute},\n day = {27},\n id = {2f8b2524-c1ad-395e-afad-243e78dd63ef},\n created = {2018-03-31T23:54:09.637Z},\n accessed = {2018-03-31},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},\n last_modified = {2018-03-31T23:54:09.637Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {There are several formalisms that enhance Bayesian networks by including relations amongst individuals as modeling primitives. For instance, Probabilistic Relational Models (PRMs) use diagrams and relational databases to represent repetitive Bayesian networks, while Relational Bayesian Networks (RBNs) employ first-order probability formulas with the same purpose. We examine the coherence checking problem for those formalisms; that is, the problem of guaranteeing that any grounding of a well-formed set of sentences does produce a valid Bayesian network. This is a novel version of de Finetti’s problem of coherence checking for probabilistic assessments. We show how to reduce the coherence checking problem in relational Bayesian networks to a validity problem in first-order logic augmented with a transitive closure operator and how to combine this logic-based approach with faster, but incomplete algorithms.},\n bibtype = {article},\n author = {De Bona, Glauber and Cozman, Fabio},\n doi = {10.3390/e20040229},\n journal = {Entropy},\n number = {4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  There are several formalisms that enhance Bayesian networks by including relations amongst individuals as modeling primitives. For instance, Probabilistic Relational Models (PRMs) use diagrams and relational databases to represent repetitive Bayesian networks, while Relational Bayesian Networks (RBNs) employ first-order probability formulas with the same purpose. We examine the coherence checking problem for those formalisms; that is, the problem of guaranteeing that any grounding of a well-formed set of sentences does produce a valid Bayesian network. This is a novel version of de Finetti’s problem of coherence checking for probabilistic assessments. We show how to reduce the coherence checking problem in relational Bayesian networks to a validity problem in first-order logic augmented with a transitive closure operator and how to combine this logic-based approach with faster, but incomplete algorithms.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"dewaal-yoo-latentvariablebayesiannetworksconstructedusingstructuralequationmodelling-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://ieeexplore.ieee.org/document/8455240/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'dewaal-yoo-latentvariablebayesiannetworksconstructedusingstructuralequationmodelling-2018', 'https://ieeexplore.ieee.org/document/8455240/', event);\">\n    Latent Variable Bayesian Networks Constructed Using Structural Equation Modelling.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  de Waal,  A.;  and Yoo,  K.\n</span>\n\n  \n\n</span>\n\n  In <i>2018 21st International Conference on Information Fusion (FUSION)</i>, pages 688-695, 7 2018. IEEE\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://ieeexplore.ieee.org/document/8455240/\"\n     onclick=\"log_download('dewaal-yoo-latentvariablebayesiannetworksconstructedusingstructuralequationmodelling-2018', 'https://ieeexplore.ieee.org/document/8455240/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Latent Variable Bayesian Networks Constructed Using Structural Equation Modelling [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.23919/ICIF.2018.8455240\"\n     onclick=\"log_download('dewaal-yoo-latentvariablebayesiannetworksconstructedusingstructuralequationmodelling-2018', 'http://doi.org/10.23919/ICIF.2018.8455240', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/dewaal-yoo-latentvariablebayesiannetworksconstructedusingstructuralequationmodelling-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('dewaal-yoo-latentvariablebayesiannetworksconstructedusingstructuralequationmodelling-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Latent Variable Bayesian Networks Constructed Using Structural Equation Modelling},\n type = {inproceedings},\n year = {2018},\n pages = {688-695},\n websites = {https://ieeexplore.ieee.org/document/8455240/},\n month = {7},\n publisher = {IEEE},\n city = {Cambridge, United Kingdom},\n id = {0f7fe6a9-391e-3ff4-922d-fcef13ddb163},\n created = {2018-09-18T12:20:19.813Z},\n accessed = {2018-09-16},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},\n last_modified = {2018-09-18T12:20:19.813Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Bayesian networks in fusion systems often contain latent variables. They play an important role in fusion systems as they provide context which lead to better choices of data sources to fuse. Latent variables in Bayesian networks are mostly constructed by means of expert knowledge modelling. We propose using theory-driven structural equation modelling (SEM) to identify and structure latent variables in a Bayesian network. The linking of SEM and Bayesian networks is motivated by the fact that both methods can be shown to be causal models. We compare this approach to a data-driven approach where latent factors are induced by means of unsupervised learning. We identify appropriate metrics for URREF ontology criteria for both annroaches.},\n bibtype = {inproceedings},\n author = {de Waal, Alta and Yoo, Keunyoung},\n doi = {10.23919/ICIF.2018.8455240},\n booktitle = {2018 21st International Conference on Information Fusion (FUSION)}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Bayesian networks in fusion systems often contain latent variables. They play an important role in fusion systems as they provide context which lead to better choices of data sources to fuse. Latent variables in Bayesian networks are mostly constructed by means of expert knowledge modelling. We propose using theory-driven structural equation modelling (SEM) to identify and structure latent variables in a Bayesian network. The linking of SEM and Bayesian networks is motivated by the fact that both methods can be shown to be causal models. We compare this approach to a data-driven approach where latent factors are induced by means of unsupervised learning. We identify appropriate metrics for URREF ontology criteria for both annroaches.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2017\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2017')\"\n      onkeypress=\"toggleGroup('group_2017')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2017</span>\n      <span class=\"bibbase_group_count\">\n        \n        (1)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"marcot-commonquandariesandtheirpracticalsolutionsinbayesiannetworkmodeling-2017\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380016308134\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'marcot-commonquandariesandtheirpracticalsolutionsinbayesiannetworkmodeling-2017', 'http://www.sciencedirect.com/science/article/pii/S0304380016308134', event);\">\n    Common quandaries and their practical solutions in Bayesian network modeling.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Marcot,  B., G.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 358: 1-9.  2017.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380016308134\"\n     onclick=\"log_download('marcot-commonquandariesandtheirpracticalsolutionsinbayesiannetworkmodeling-2017', 'http://www.sciencedirect.com/science/article/pii/S0304380016308134', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Common quandaries and their practical solutions in Bayesian network modeling [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2017.05.011\"\n     onclick=\"log_download('marcot-commonquandariesandtheirpracticalsolutionsinbayesiannetworkmodeling-2017', 'http://doi.org/10.1016/j.ecolmodel.2017.05.011', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/marcot-commonquandariesandtheirpracticalsolutionsinbayesiannetworkmodeling-2017\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('marcot-commonquandariesandtheirpracticalsolutionsinbayesiannetworkmodeling-2017')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Common quandaries and their practical solutions in Bayesian network modeling},\n type = {article},\n year = {2017},\n pages = {1-9},\n volume = {358},\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380016308134},\n id = {6f3e525f-5e99-3f8e-8111-40cdae7203dc},\n created = {2017-05-30T02:16:54.843Z},\n accessed = {2017-05-29},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},\n last_modified = {2017-05-30T02:16:54.843Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Use and popularity of Bayesian network (BN) modeling has greatly expanded in recent years, but many common problems remain. Here, I summarize key problems in BN model construction and interpretation, along with suggested practical solutions. Problems in BN model construction include parameterizing probability values, variable definition, complex network structures, latent and confounding variables, outlier expert judgments, variable correlation, model peer review, tests of calibration and validation, model overfitting, and modeling wicked problems. Problems in BN model interpretation include objective creep, misconstruing variable influence, conflating correlation with causation, conflating proportion and expectation with probability, and using expert opinion. Solutions are offered for each problem and researchers are urged to innovate and share further solutions.},\n bibtype = {article},\n author = {Marcot, Bruce G.},\n doi = {10.1016/j.ecolmodel.2017.05.011},\n journal = {Ecological Modelling}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Use and popularity of Bayesian network (BN) modeling has greatly expanded in recent years, but many common problems remain. Here, I summarize key problems in BN model construction and interpretation, along with suggested practical solutions. Problems in BN model construction include parameterizing probability values, variable definition, complex network structures, latent and confounding variables, outlier expert judgments, variable correlation, model peer review, tests of calibration and validation, model overfitting, and modeling wicked problems. Problems in BN model interpretation include objective creep, misconstruing variable influence, conflating correlation with causation, conflating proportion and expectation with probability, and using expert opinion. Solutions are offered for each problem and researchers are urged to innovate and share further solutions.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2016\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2016')\"\n      onkeypress=\"toggleGroup('group_2016')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2016</span>\n      <span class=\"bibbase_group_count\">\n        \n        (1)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"mkrtchyan-podofillini-dang-methodsforbuildingconditionalprobabilitytablesofbayesianbeliefnetworksfromlimitedjudgmentanevaluationforhumanreliabilityapplication-2016\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://linkinghub.elsevier.com/retrieve/pii/S0951832016000132\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'mkrtchyan-podofillini-dang-methodsforbuildingconditionalprobabilitytablesofbayesianbeliefnetworksfromlimitedjudgmentanevaluationforhumanreliabilityapplication-2016', 'http://linkinghub.elsevier.com/retrieve/pii/S0951832016000132', event);\">\n    Methods for building Conditional Probability Tables of Bayesian Belief Networks from limited judgment: An evaluation for Human Reliability Application.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Mkrtchyan,  L.; Podofillini,  L.;  and Dang,  V.\n</span>\n\n  \n\n</span>\n\n  <i>Reliability Engineering & System Safety</i>, 151: 93-112. 7 2016.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://linkinghub.elsevier.com/retrieve/pii/S0951832016000132\"\n     onclick=\"log_download('mkrtchyan-podofillini-dang-methodsforbuildingconditionalprobabilitytablesofbayesianbeliefnetworksfromlimitedjudgmentanevaluationforhumanreliabilityapplication-2016', 'http://linkinghub.elsevier.com/retrieve/pii/S0951832016000132', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Methods for building Conditional Probability Tables of Bayesian Belief Networks from limited judgment: An evaluation for Human Reliability Application [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ress.2016.01.004\"\n     onclick=\"log_download('mkrtchyan-podofillini-dang-methodsforbuildingconditionalprobabilitytablesofbayesianbeliefnetworksfromlimitedjudgmentanevaluationforhumanreliabilityapplication-2016', 'http://doi.org/10.1016/j.ress.2016.01.004', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/mkrtchyan-podofillini-dang-methodsforbuildingconditionalprobabilitytablesofbayesianbeliefnetworksfromlimitedjudgmentanevaluationforhumanreliabilityapplication-2016\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('mkrtchyan-podofillini-dang-methodsforbuildingconditionalprobabilitytablesofbayesianbeliefnetworksfromlimitedjudgmentanevaluationforhumanreliabilityapplication-2016')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Methods for building Conditional Probability Tables of Bayesian Belief Networks from limited judgment: An evaluation for Human Reliability Application},\n type = {article},\n year = {2016},\n pages = {93-112},\n volume = {151},\n websites = {http://linkinghub.elsevier.com/retrieve/pii/S0951832016000132},\n month = {7},\n publisher = {Elsevier Ltd},\n id = {ea427921-cd23-3157-b5f0-ba00af919c18},\n created = {2017-06-01T01:04:09.750Z},\n accessed = {2017-05-31},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},\n last_modified = {2017-06-01T01:04:09.750Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n bibtype = {article},\n author = {Mkrtchyan, L. and Podofillini, L. and Dang, V.N.},\n doi = {10.1016/j.ress.2016.01.004},\n journal = {Reliability Engineering &amp; System Safety}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2014\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2014')\"\n      onkeypress=\"toggleGroup('group_2014')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2014</span>\n      <span class=\"bibbase_group_count\">\n        \n        (1)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"yet-perkins-fenton-tai-marsh-notjustdataamethodforimprovingpredictionwithknowledge-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1532046413001640\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'yet-perkins-fenton-tai-marsh-notjustdataamethodforimprovingpredictionwithknowledge-2014', 'http://www.sciencedirect.com/science/article/pii/S1532046413001640', event);\">\n    Not just data: a method for improving prediction with knowledge.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Yet,  B.; Perkins,  Z.; Fenton,  N.; Tai,  N.;  and Marsh,  W.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of biomedical informatics</i>, 48: 28-37. 4 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1532046413001640\"\n     onclick=\"log_download('yet-perkins-fenton-tai-marsh-notjustdataamethodforimprovingpredictionwithknowledge-2014', 'http://www.sciencedirect.com/science/article/pii/S1532046413001640', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Not just data: a method for improving prediction with knowledge. [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.jbi.2013.10.012\"\n     onclick=\"log_download('yet-perkins-fenton-tai-marsh-notjustdataamethodforimprovingpredictionwithknowledge-2014', 'http://doi.org/10.1016/j.jbi.2013.10.012', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/yet-perkins-fenton-tai-marsh-notjustdataamethodforimprovingpredictionwithknowledge-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>1 download</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('yet-perkins-fenton-tai-marsh-notjustdataamethodforimprovingpredictionwithknowledge-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Not just data: a method for improving prediction with knowledge.},\n type = {article},\n year = {2014},\n keywords = {Algorithms,Bayes Theorem,Blood Coagulation,Blood Coagulation Disorders,Blood Coagulation Disorders: therapy,Cluster Analysis,Decision Making,Decision Support Systems, Clinical,Diagnosis, Computer-Assisted,Emergency Medical Services,Emergency Medical Services: organization &amp; adminis,Humans,Medical Errors,Medical Errors: prevention &amp; control,Medical Informatics,Medical Informatics: methods,Medical Informatics: trends,Risk Assessment,Sensitivity and Specificity},\n pages = {28-37},\n volume = {48},\n websites = {http://www.sciencedirect.com/science/article/pii/S1532046413001640},\n month = {4},\n id = {a9159f5c-4a66-3b17-a9fb-7f0b441cf0f2},\n created = {2015-04-12T20:17:35.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},\n last_modified = {2017-03-14T14:39:09.523Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Many medical conditions are only indirectly observed through symptoms and tests. Developing predictive models for such conditions is challenging since they can be thought of as &#x27;latent&#x27; variables. They are not present in the data and often get confused with measurements. As a result, building a model that fits data well is not the same as making a prediction that is useful for decision makers. In this paper, we present a methodology for developing Bayesian network (BN) models that predict and reason with latent variables, using a combination of expert knowledge and available data. The method is illustrated by a case study into the prediction of acute traumatic coagulopathy (ATC), a disorder of blood clotting that significantly increases the risk of death following traumatic injuries. There are several measurements for ATC and previous models have predicted one of these measurements instead of the state of ATC itself. Our case study illustrates the advantages of models that distinguish between an underlying latent condition and its measurements, and of a continuing dialogue between the modeller and the domain experts as the model is developed using knowledge as well as data.},\n bibtype = {article},\n author = {Yet, Barbaros and Perkins, Zane and Fenton, Norman and Tai, Nigel and Marsh, William},\n doi = {10.1016/j.jbi.2013.10.012},\n journal = {Journal of biomedical informatics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Many medical conditions are only indirectly observed through symptoms and tests. Developing predictive models for such conditions is challenging since they can be thought of as 'latent' variables. They are not present in the data and often get confused with measurements. As a result, building a model that fits data well is not the same as making a prediction that is useful for decision makers. In this paper, we present a methodology for developing Bayesian network (BN) models that predict and reason with latent variables, using a combination of expert knowledge and available data. The method is illustrated by a case study into the prediction of acute traumatic coagulopathy (ATC), a disorder of blood clotting that significantly increases the risk of death following traumatic injuries. There are several measurements for ATC and previous models have predicted one of these measurements instead of the state of ATC itself. Our case study illustrates the advantages of models that distinguish between an underlying latent condition and its measurements, and of a continuing dialogue between the modeller and the domain experts as the model is developed using knowledge as well as data.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2010\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2010')\"\n      onkeypress=\"toggleGroup('group_2010')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2010</span>\n      <span class=\"bibbase_group_count\">\n        \n        (1)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"johnson-mengersen-dewaal-marnewick-cilliers-houser-boast-modellingcheetahrelocationsuccessinsouthernafricausinganiterativebayesiannetworkdevelopmentcycle-2010\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380009007947\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'johnson-mengersen-dewaal-marnewick-cilliers-houser-boast-modellingcheetahrelocationsuccessinsouthernafricausinganiterativebayesiannetworkdevelopmentcycle-2010', 'http://www.sciencedirect.com/science/article/pii/S0304380009007947', event);\">\n    Modelling cheetah relocation success in southern Africa using an Iterative Bayesian Network Development Cycle.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Johnson,  S.; Mengersen,  K.; de Waal,  A.; Marnewick,  K.; Cilliers,  D.; Houser,  A., M.;  and Boast,  L.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 221(4): 641-651. 2 2010.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380009007947\"\n     onclick=\"log_download('johnson-mengersen-dewaal-marnewick-cilliers-houser-boast-modellingcheetahrelocationsuccessinsouthernafricausinganiterativebayesiannetworkdevelopmentcycle-2010', 'http://www.sciencedirect.com/science/article/pii/S0304380009007947', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Modelling cheetah relocation success in southern Africa using an Iterative Bayesian Network Development Cycle [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2009.11.012\"\n     onclick=\"log_download('johnson-mengersen-dewaal-marnewick-cilliers-houser-boast-modellingcheetahrelocationsuccessinsouthernafricausinganiterativebayesiannetworkdevelopmentcycle-2010', 'http://doi.org/10.1016/j.ecolmodel.2009.11.012', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/johnson-mengersen-dewaal-marnewick-cilliers-houser-boast-modellingcheetahrelocationsuccessinsouthernafricausinganiterativebayesiannetworkdevelopmentcycle-2010\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('johnson-mengersen-dewaal-marnewick-cilliers-houser-boast-modellingcheetahrelocationsuccessinsouthernafricausinganiterativebayesiannetworkdevelopmentcycle-2010')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Modelling cheetah relocation success in southern Africa using an Iterative Bayesian Network Development Cycle},\n type = {article},\n year = {2010},\n keywords = {Acinonyx jubatus,Bayesian network,Cheetah metapopulation,IBNDC,Iterative approach,Predator human conflict,Relocation},\n pages = {641-651},\n volume = {221},\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380009007947},\n month = {2},\n id = {c05397ed-419b-34d5-b96a-cde7ecbe833c},\n created = {2015-04-12T18:59:39.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {61ffc698-847a-3a7c-87f9-86532b1ed07b},\n last_modified = {2017-03-14T14:39:09.523Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Relocation is one of the strategies used by conservationists to deal with problem cheetahs in southern Africa. The success of a relocation event and the factors that influence it within the broader context of long-term viability of wild cheetah metapopulations was the focus of a Bayesian Network (BN) modelling workshop in South Africa. Using a new heuristics, Iterative Bayesian Network Development Cycle (IBNDC), described in this paper, several networks were formulated to distinguish between the unique relocation experiences and conditions in Botswana and South Africa. There were many common underlying factors, despite the disparate relocation strategies and sites in the two countries. The benefit of relocation BNs goes beyond the identification and quantification of the factors influencing the success of relocations and population viability. They equip conservationists with a powerful communication tool in their negotiations with land and livestock owners, which is key to the long-term survival of cheetahs in southern Africa. Importantly, the IBNDC provides the ecological modeller with a methodological process that combines several BN design frameworks to facilitate the development of a BN in a multi-expert and multi-field domain.},\n bibtype = {article},\n author = {Johnson, Sandra and Mengersen, Kerrie and de Waal, Alta and Marnewick, Kelly and Cilliers, Deon and Houser, Ann Marie and Boast, Lorraine},\n doi = {10.1016/j.ecolmodel.2009.11.012},\n journal = {Ecological Modelling},\n number = {4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Relocation is one of the strategies used by conservationists to deal with problem cheetahs in southern Africa. The success of a relocation event and the factors that influence it within the broader context of long-term viability of wild cheetah metapopulations was the focus of a Bayesian Network (BN) modelling workshop in South Africa. Using a new heuristics, Iterative Bayesian Network Development Cycle (IBNDC), described in this paper, several networks were formulated to distinguish between the unique relocation experiences and conditions in Botswana and South Africa. There were many common underlying factors, despite the disparate relocation strategies and sites in the two countries. The benefit of relocation BNs goes beyond the identification and quantification of the factors influencing the success of relocations and population viability. They equip conservationists with a powerful communication tool in their negotiations with land and livestock owners, which is key to the long-term survival of cheetahs in southern Africa. Importantly, the IBNDC provides the ecological modeller with a methodological process that combines several BN design frameworks to facilitate the development of a BN in a multi-expert and multi-field domain.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n\n\n\n  </div>\n\n\n  <!-- Modal -->\n\n  <!-- <iframe id=\"bibbase_network_frame\" -->\n  <!--         src=\"//bibbase.org/network/control\" -->\n  <!--         style=\"display: none;\"> -->\n  <!-- </iframe> -->\n\n</div>\n"}; document.write(bibbase_data.data);