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: [{\"type\":\"inbook\",\"year\":\"2018\",\"keywords\":\"Biometric identification,Cardiac murmur,Electrocardiographic signal,Signal processing\",\"pages\":\"410-418\",\"websites\":\"http://link.springer.com/10.1007/978-3-030-03493-1_43\",\"id\":\"0279fa9d-7b7e-3561-b8f8-18cbe6d222f1\",\"created\":\"2021-02-10T05:25:38.895Z\",\"file_attached\":false,\"profile_id\":\"dcbddeb4-43a7-32ca-8726-8f47f33c5362\",\"last_modified\":\"2021-02-10T05:25:38.895Z\",\"read\":false,\"starred\":false,\"authored\":\"true\",\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Becerra2018\",\"private_publication\":false,\"abstract\":\"The process of distinguishing among human beings through the inspection of acquired data from physical or behavioral traits is known as biometric identification. Mostly, fingerprint- and iris-based biometric techniques are used. Nowadays, since such techniques are highly susceptible to be counterfeited, new biometric alternatives are explored mainly based on physiological signals and behavioral traits -which are useful not only for biometric identification purposes, but may also play a role as a vital signal indicator. In this connection, the electrocardiographic (ECG) signals have shown to be a suitable approach. Nonetheless, their informative components (morphology, rhythm, polarization, and among others) can be affected by the presence of a cardiac pathology. Even more, some other cardiac diseases cannot directly be detected by the ECG signal inspection but still have an effect on their waveform, that is the case of cardiac murmurs. Therefore, for biometric purposes, such signals should be analyzed submitted to the effects of pathologies. This paper presents a exploratory study aimed at assessing the influence of the presence of a pathology when analyzing ECG signals for implementing a biometric system. For experiments, a data base holding 20 healthy subjects and 20 pathological subjects (diagnosed with different types of cardiac murmurs) are considered. The proposed signal analysis consists of preprocessing, characterization (using wavelet features), feature selection and classification (five classifiers as well as a mixture of them are tested). As a result, through the performed comparison of the classification rates when testing pathological and normal ECG signals, the cardiac murmurs’ undesired effect on the identification mechanism performance is clearly unveiled.\",\"bibtype\":\"inbook\",\"author\":\"Becerra, M. A. and Duque-Mejía, C. and Zapata-Hernández, C. and Peluffo-Ordóñez, D. H. and Serna-Guarín, L. and Delgado-Trejos, Edilson and Revelo-Fuelagán, E. J. and Blanco Valencia, X. P.\",\"doi\":\"10.1007/978-3-030-03493-1_43\",\"chapter\":\"Exploratory Study of the Effects of Cardiac Murmurs on Electrocardiographic-Signal-Based Biometric Systems\",\"title\":\"Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)\",\"bibtex\":\"@inbook{\\n type = {inbook},\\n year = {2018},\\n keywords = {Biometric identification,Cardiac murmur,Electrocardiographic signal,Signal processing},\\n pages = {410-418},\\n websites = {http://link.springer.com/10.1007/978-3-030-03493-1_43},\\n id = {0279fa9d-7b7e-3561-b8f8-18cbe6d222f1},\\n created = {2021-02-10T05:25:38.895Z},\\n file_attached = {false},\\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\\n last_modified = {2021-02-10T05:25:38.895Z},\\n read = {false},\\n starred = {false},\\n authored = {true},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Becerra2018},\\n private_publication = {false},\\n abstract = {The process of distinguishing among human beings through the inspection of acquired data from physical or behavioral traits is known as biometric identification. Mostly, fingerprint- and iris-based biometric techniques are used. Nowadays, since such techniques are highly susceptible to be counterfeited, new biometric alternatives are explored mainly based on physiological signals and behavioral traits -which are useful not only for biometric identification purposes, but may also play a role as a vital signal indicator. In this connection, the electrocardiographic (ECG) signals have shown to be a suitable approach. Nonetheless, their informative components (morphology, rhythm, polarization, and among others) can be affected by the presence of a cardiac pathology. Even more, some other cardiac diseases cannot directly be detected by the ECG signal inspection but still have an effect on their waveform, that is the case of cardiac murmurs. Therefore, for biometric purposes, such signals should be analyzed submitted to the effects of pathologies. This paper presents a exploratory study aimed at assessing the influence of the presence of a pathology when analyzing ECG signals for implementing a biometric system. For experiments, a data base holding 20 healthy subjects and 20 pathological subjects (diagnosed with different types of cardiac murmurs) are considered. The proposed signal analysis consists of preprocessing, characterization (using wavelet features), feature selection and classification (five classifiers as well as a mixture of them are tested). As a result, through the performed comparison of the classification rates when testing pathological and normal ECG signals, the cardiac murmurs’ undesired effect on the identification mechanism performance is clearly unveiled.},\\n bibtype = {inbook},\\n author = {Becerra, M. A. and Duque-Mejía, C. and Zapata-Hernández, C. and Peluffo-Ordóñez, D. H. and Serna-Guarín, L. and Delgado-Trejos, Edilson and Revelo-Fuelagán, E. J. and Blanco Valencia, X. P.},\\n doi = {10.1007/978-3-030-03493-1_43},\\n chapter = {Exploratory Study of the Effects of Cardiac Murmurs on Electrocardiographic-Signal-Based Biometric Systems},\\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\\n}\",\"author_short\":[\"Becerra,  M., A.\",\"Duque-Mejía,  C.\",\"Zapata-Hernández,  C.\",\"Peluffo-Ordóñez,  D., H.\",\"Serna-Guarín,  L.\",\"Delgado-Trejos,  E.\",\"Revelo-Fuelagán,  E., J.\",\"Blanco Valencia,  X., P.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/978-3-030-03493-1_43\"},\"biburl\":\"https://bibbase.org/service/mendeley/dcbddeb4-43a7-32ca-8726-8f47f33c5362\",\"bibbaseid\":\"becerra-duquemeja-zapatahernndez-peluffoordez-sernaguarn-delgadotrejos-revelofuelagn-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2018\",\"role\":\"author\",\"keyword\":[\"Biometric identification\",\"Cardiac murmur\",\"Electrocardiographic signal\",\"Signal processing\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"type\":\"inbook\",\"year\":\"2018\",\"keywords\":\"Dimensionality reduction,Generalized methodology,Kernel approximations,Low-computational cost,Multiple kernel learning,Spectral methods\",\"pages\":\"661-669\",\"websites\":\"http://link.springer.com/10.1007/978-3-030-03493-1_69\",\"id\":\"64e2b849-aef0-35d8-861a-b2b29cf9315f\",\"created\":\"2021-02-10T05:25:38.898Z\",\"file_attached\":false,\"profile_id\":\"dcbddeb4-43a7-32ca-8726-8f47f33c5362\",\"last_modified\":\"2021-02-10T05:25:38.898Z\",\"read\":false,\"starred\":false,\"authored\":\"true\",\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Salazar-Castro2018\",\"private_publication\":false,\"abstract\":\"Dimensionality reduction (DR) is a methodology used in many fields linked to data processing, and may represent a preprocessing stage or be an essential element for the representation and classification of data. The main objective of DR is to obtain a new representation of the original data in a space of smaller dimension, such that more refined information is produced, as well as the time of the subsequent processing is decreased and/or visual representations more intelligible for human beings are generated. The spectral DR methods involve the calculation of an eigenvalue and eigenvector decomposition, which is usually high-computational-cost demanding, and, therefore, the task of obtaining a more dynamic and interactive user-machine integration is difficult. Therefore, for the design of an interactive IV system based on DR spectral methods, it is necessary to propose a strategy to reduce the computational cost required in the calculation of eigenvectors and eigenvalues. For this purpose, it is proposed to use locally linear submatrices and spectral embedding. This allows integrating natural intelligence with computational intelligence for the representation of data interactively, dynamically and at low computational cost. Additionally, an interactive model is proposed that allows the user to dynamically visualize the data through a weighted mixture.\",\"bibtype\":\"inbook\",\"author\":\"Salazar-Castro, J. A. and Peña, D. F. and Basante, C. and Ortega, C. and Cruz-Cruz, L. and Revelo-Fuelagán, J. and Blanco-Valencia, X. P. and Castellanos-Domínguez, G. and Peluffo-Ordóñez, D. H.\",\"doi\":\"10.1007/978-3-030-03493-1_69\",\"chapter\":\"Generalized Low-Computational Cost Laplacian Eigenmaps\",\"title\":\"Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)\",\"bibtex\":\"@inbook{\\n type = {inbook},\\n year = {2018},\\n keywords = {Dimensionality reduction,Generalized methodology,Kernel approximations,Low-computational cost,Multiple kernel learning,Spectral methods},\\n pages = {661-669},\\n websites = {http://link.springer.com/10.1007/978-3-030-03493-1_69},\\n id = {64e2b849-aef0-35d8-861a-b2b29cf9315f},\\n created = {2021-02-10T05:25:38.898Z},\\n file_attached = {false},\\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\\n last_modified = {2021-02-10T05:25:38.898Z},\\n read = {false},\\n starred = {false},\\n authored = {true},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Salazar-Castro2018},\\n private_publication = {false},\\n abstract = {Dimensionality reduction (DR) is a methodology used in many fields linked to data processing, and may represent a preprocessing stage or be an essential element for the representation and classification of data. 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This allows integrating natural intelligence with computational intelligence for the representation of data interactively, dynamically and at low computational cost. Additionally, an interactive model is proposed that allows the user to dynamically visualize the data through a weighted mixture.},\\n bibtype = {inbook},\\n author = {Salazar-Castro, J. A. and Peña, D. F. and Basante, C. and Ortega, C. and Cruz-Cruz, L. and Revelo-Fuelagán, J. and Blanco-Valencia, X. P. and Castellanos-Domínguez, G. and Peluffo-Ordóñez, D. 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E. and Lorente-Leyva, Leandro L.\",\"doi\":\"10.1007/978-3-030-14799-0_29\",\"chapter\":\"Adaptation and Recovery Stages for Case-Based Reasoning Systems Using Bayesian Estimation and Density Estimation with Nearest Neighbors\",\"title\":\"Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)\",\"bibtex\":\"@inbook{\\n type = {inbook},\\n year = {2019},\\n keywords = {Bayes,Case-based reasoning,Classification,Parametric,Probability},\\n pages = {339-350},\\n websites = {http://link.springer.com/10.1007/978-3-030-14799-0_29},\\n id = {cb30131d-ab87-3ed0-b26f-4004b13ee7e6},\\n created = {2021-02-10T05:25:38.975Z},\\n file_attached = {false},\\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\\n last_modified = {2021-02-10T05:25:38.975Z},\\n read = {false},\\n starred = {false},\\n authored = {true},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {BastidasTorres2019},\\n private_publication = {false},\\n abstract = {When searching for better solutions that improve the medical diagnosis accuracy, Case-Based reasoning systems (CBR) arise as a good option. 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E. and Lorente-Leyva, Leandro L.},\\n doi = {10.1007/978-3-030-14799-0_29},\\n chapter = {Adaptation and Recovery Stages for Case-Based Reasoning Systems Using Bayesian Estimation and Density Estimation with Nearest Neighbors},\\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\\n}\",\"author_short\":[\"Bastidas Torres,  D.\",\"Piñeros Rodriguez,  C.\",\"Peluffo-Ordóñez,  D., H.\",\"Blanco Valencia,  X.\",\"Revelo-Fuelagán,  J.\",\"Becerra,  M., A.\",\"Castro-Ospina,  A., E.\",\"Lorente-Leyva,  L., L.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/978-3-030-14799-0_29\"},\"biburl\":\"https://bibbase.org/service/mendeley/dcbddeb4-43a7-32ca-8726-8f47f33c5362\",\"bibbaseid\":\"bastidastorres-pierosrodriguez-peluffoordez-blancovalencia-revelofuelagn-becerra-castroospina-lorenteleyva-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019\",\"role\":\"author\",\"keyword\":[\"Bayes\",\"Case-based reasoning\",\"Classification\",\"Parametric\",\"Probability\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"type\":\"inbook\",\"year\":\"2016\",\"keywords\":\"Dimensionality reduction,Generalized kernel formulation,Kernel PCA,Spectral clustering,Support vector machine\",\"pages\":\"255-264\",\"websites\":\"http://link.springer.com/10.1007/978-3-319-40162-1_28\",\"id\":\"2f1f2725-75df-38fe-a220-32d52511547c\",\"created\":\"2021-02-10T05:25:38.981Z\",\"file_attached\":false,\"profile_id\":\"dcbddeb4-43a7-32ca-8726-8f47f33c5362\",\"last_modified\":\"2021-02-10T05:25:38.981Z\",\"read\":false,\"starred\":false,\"authored\":\"true\",\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Peluffo-Ordonez2016\",\"source_type\":\"incollection\",\"private_publication\":false,\"abstract\":\"This paper presents the development of a unified view of spectral clustering and unsupervised dimensionality reduction approaches within a generalized kernel framework. To do so, the authors propose a multipurpose latent variable model in terms of a high-dimensional representation of the input data matrix, which is incorporated into a least-squares support vector machine to yield a generalized optimization problem. After solving it via a primal-dual procedure, the final model results in a versatile projected matrix able to represent data in a low-dimensional space, as well as to provide information about clusters. Specifically, our formulation yields solutions for kernel spectral clustering and weighted-kernel principal component analysis.\",\"bibtype\":\"inbook\",\"author\":\"Peluffo-Ordóñez, D H and Becerra, M A and Castro-Ospina, A E and Blanco-Valencia, X and Alvarado-Pérez, J C and Therón, R and Anaya-Isaza, A\",\"doi\":\"10.1007/978-3-319-40162-1_28\",\"chapter\":\"On the Relationship Between Dimensionality Reduction and Spectral Clustering from a Kernel Viewpoint\",\"title\":\"Advances in Intelligent Systems and Computing\",\"bibtex\":\"@inbook{\\n type = {inbook},\\n year = {2016},\\n keywords = {Dimensionality reduction,Generalized kernel formulation,Kernel PCA,Spectral clustering,Support vector machine},\\n pages = {255-264},\\n websites = {http://link.springer.com/10.1007/978-3-319-40162-1_28},\\n id = {2f1f2725-75df-38fe-a220-32d52511547c},\\n created = {2021-02-10T05:25:38.981Z},\\n file_attached = {false},\\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\\n last_modified = {2021-02-10T05:25:38.981Z},\\n read = {false},\\n starred = {false},\\n authored = {true},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Peluffo-Ordonez2016},\\n source_type = {incollection},\\n private_publication = {false},\\n abstract = {This paper presents the development of a unified view of spectral clustering and unsupervised dimensionality reduction approaches within a generalized kernel framework. To do so, the authors propose a multipurpose latent variable model in terms of a high-dimensional representation of the input data matrix, which is incorporated into a least-squares support vector machine to yield a generalized optimization problem. After solving it via a primal-dual procedure, the final model results in a versatile projected matrix able to represent data in a low-dimensional space, as well as to provide information about clusters. Specifically, our formulation yields solutions for kernel spectral clustering and weighted-kernel principal component analysis.},\\n bibtype = {inbook},\\n author = {Peluffo-Ordóñez, D H and Becerra, M A and Castro-Ospina, A E and Blanco-Valencia, X and Alvarado-Pérez, J C and Therón, R and Anaya-Isaza, A},\\n doi = {10.1007/978-3-319-40162-1_28},\\n chapter = {On the Relationship Between Dimensionality Reduction and Spectral Clustering from a Kernel Viewpoint},\\n title = {Advances in Intelligent Systems and Computing}\\n}\",\"author_short\":[\"Peluffo-Ordóñez,  D., H.\",\"Becerra,  M., A.\",\"Castro-Ospina,  A., E.\",\"Blanco-Valencia,  X.\",\"Alvarado-Pérez,  J., C.\",\"Therón,  R.\",\"Anaya-Isaza,  A.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/978-3-319-40162-1_28\"},\"biburl\":\"https://bibbase.org/service/mendeley/dcbddeb4-43a7-32ca-8726-8f47f33c5362\",\"bibbaseid\":\"peluffoordez-becerra-castroospina-blancovalencia-alvaradoprez-thern-anayaisaza-advancesinintelligentsystemsandcomputing-2016\",\"role\":\"author\",\"keyword\":[\"Dimensionality reduction\",\"Generalized kernel formulation\",\"Kernel PCA\",\"Spectral clustering\",\"Support vector machine\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":1,\"html\":\"\"},{\"type\":\"inbook\",\"year\":\"2018\",\"keywords\":\"Cascade classification,Case-based reasoning,Preprocessing,Probability\",\"pages\":\"26-38\",\"websites\":\"http://link.springer.com/10.1007/978-3-319-78723-7_3\",\"id\":\"3351c72f-385f-3d27-b040-6be78e4e691d\",\"created\":\"2021-02-10T05:25:38.984Z\",\"file_attached\":false,\"profile_id\":\"dcbddeb4-43a7-32ca-8726-8f47f33c5362\",\"last_modified\":\"2021-02-10T05:25:38.984Z\",\"read\":false,\"starred\":false,\"authored\":\"true\",\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"BlancoValencia2018\",\"private_publication\":false,\"abstract\":\"Case-Based Reasoning Systems (CBR) are in constant evolution, as a result, this article proposes improving the retrieve and adaption stages through a different approach. A series of experiments were made, divided in three sections: a proper pre-processing technique, a cascade classification, and a probability estimation procedure. Every stage offers an improvement, a better data representation, a more efficient classification, and a more precise probability estimation provided by a Support Vector Machine (SVM) estimator regarding more common approaches. Concluding, more complex techniques for classification and probability estimation are possible, improving CBR systems performance due to lower classification error in general cases.\",\"bibtype\":\"inbook\",\"author\":\"Blanco Valencia, X. and Bastidas Torres, D. and Piñeros Rodriguez, C. and Peluffo-Ordóñez, D. H. and Becerra, M. A. and Castro-Ospina, A. E.\",\"doi\":\"10.1007/978-3-319-78723-7_3\",\"chapter\":\"Case-Based Reasoning Systems for Medical Applications with Improved Adaptation and Recovery Stages\",\"title\":\"Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)\",\"bibtex\":\"@inbook{\\n type = {inbook},\\n year = {2018},\\n keywords = {Cascade classification,Case-based reasoning,Preprocessing,Probability},\\n pages = {26-38},\\n websites = {http://link.springer.com/10.1007/978-3-319-78723-7_3},\\n id = {3351c72f-385f-3d27-b040-6be78e4e691d},\\n created = {2021-02-10T05:25:38.984Z},\\n file_attached = {false},\\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\\n last_modified = {2021-02-10T05:25:38.984Z},\\n read = {false},\\n starred = {false},\\n authored = {true},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {BlancoValencia2018},\\n private_publication = {false},\\n abstract = {Case-Based Reasoning Systems (CBR) are in constant evolution, as a result, this article proposes improving the retrieve and adaption stages through a different approach. A series of experiments were made, divided in three sections: a proper pre-processing technique, a cascade classification, and a probability estimation procedure. Every stage offers an improvement, a better data representation, a more efficient classification, and a more precise probability estimation provided by a Support Vector Machine (SVM) estimator regarding more common approaches. Concluding, more complex techniques for classification and probability estimation are possible, improving CBR systems performance due to lower classification error in general cases.},\\n bibtype = {inbook},\\n author = {Blanco Valencia, X. and Bastidas Torres, D. and Piñeros Rodriguez, C. and Peluffo-Ordóñez, D. H. and Becerra, M. A. and Castro-Ospina, A. E.},\\n doi = {10.1007/978-3-319-78723-7_3},\\n chapter = {Case-Based Reasoning Systems for Medical Applications with Improved Adaptation and Recovery Stages},\\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\\n}\",\"author_short\":[\"Blanco Valencia,  X.\",\"Bastidas Torres,  D.\",\"Piñeros Rodriguez,  C.\",\"Peluffo-Ordóñez,  D., H.\",\"Becerra,  M., A.\",\"Castro-Ospina,  A., E.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/978-3-319-78723-7_3\"},\"biburl\":\"https://bibbase.org/service/mendeley/dcbddeb4-43a7-32ca-8726-8f47f33c5362\",\"bibbaseid\":\"blancovalencia-bastidastorres-pierosrodriguez-peluffoordez-becerra-castroospina-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2018\",\"role\":\"author\",\"keyword\":[\"Cascade classification\",\"Case-based reasoning\",\"Preprocessing\",\"Probability\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Razonamiento basado en casos aplicado al diagnóstico médico utilizando clasificadores multi-clase: Un estudio preliminar\",\"type\":\"article\",\"year\":\"2017\",\"pages\":\"232-243\",\"volume\":\"8\",\"websites\":\"https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/141\",\"month\":\"2\",\"id\":\"1160d31c-9bc4-3569-b3e6-51a813010744\",\"created\":\"2021-02-10T05:25:39.004Z\",\"file_attached\":false,\"profile_id\":\"dcbddeb4-43a7-32ca-8726-8f47f33c5362\",\"last_modified\":\"2021-02-10T05:25:39.004Z\",\"read\":false,\"starred\":false,\"authored\":\"true\",\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Viveros-Melo2017\",\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"CBR ha demostrado ser apropiado para trabajar con datos de dominios poco estructurados o situaciones donde es difícil la adquisición de conocimiento, como es el caso del diagnóstico médico, donde es posible identificar enfermedades como: cáncer, predicción de epilepsia y diagnóstico de apendicitis. Algunas de las tendencias que se pueden desarrollar para CBR en la ciencia de la salud están orientadas a reducir el número de características en datos de gran dimensión. Una contribución importante puede ser la estimación de probabilidades de pertenencia a cada clase para los nuevos casos. Con el fin de representar adecuadamente la base de datos y evitar los inconvenientes causados por la alta dimensión, ruido y redundancia de los mimos, en este trabajo, se utiliza varios algoritmos en la etapa de pre-procesamiento para realizar una selección de variables y reducción de dimensiones. Además, se realiza una comparación del rendimiento de algunos clasificadores multi-clase representativos para identificar el más eficaz e incluirlo en un esquema CBR. En particular, se emplean cuatro técnicas de clasificación y dos técnicas de reducción para hacer un estudio comparativo de clasificadores multi-clase sobre CBR\",\"bibtype\":\"article\",\"author\":\"Viveros-Melo, D and Ortega-Adarme, M and Blanco Valencia, X and Castro-Ospina, A E and Murillo Rendón, S and Peluffo-Ordóñez, D H\",\"doi\":\"10.29019/enfoqueute.v8n1.141\",\"journal\":\"Enfoque UTE\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {Razonamiento basado en casos aplicado al diagnóstico médico utilizando clasificadores multi-clase: Un estudio preliminar},\\n type = {article},\\n year = {2017},\\n pages = {232-243},\\n volume = {8},\\n websites = {https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/141},\\n month = {2},\\n id = {1160d31c-9bc4-3569-b3e6-51a813010744},\\n created = {2021-02-10T05:25:39.004Z},\\n file_attached = {false},\\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\\n last_modified = {2021-02-10T05:25:39.004Z},\\n read = {false},\\n starred = {false},\\n authored = {true},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Viveros-Melo2017},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {CBR ha demostrado ser apropiado para trabajar con datos de dominios poco estructurados o situaciones donde es difícil la adquisición de conocimiento, como es el caso del diagnóstico médico, donde es posible identificar enfermedades como: cáncer, predicción de epilepsia y diagnóstico de apendicitis. Algunas de las tendencias que se pueden desarrollar para CBR en la ciencia de la salud están orientadas a reducir el número de características en datos de gran dimensión. Una contribución importante puede ser la estimación de probabilidades de pertenencia a cada clase para los nuevos casos. Con el fin de representar adecuadamente la base de datos y evitar los inconvenientes causados por la alta dimensión, ruido y redundancia de los mimos, en este trabajo, se utiliza varios algoritmos en la etapa de pre-procesamiento para realizar una selección de variables y reducción de dimensiones. Además, se realiza una comparación del rendimiento de algunos clasificadores multi-clase representativos para identificar el más eficaz e incluirlo en un esquema CBR. En particular, se emplean cuatro técnicas de clasificación y dos técnicas de reducción para hacer un estudio comparativo de clasificadores multi-clase sobre CBR},\\n bibtype = {article},\\n author = {Viveros-Melo, D and Ortega-Adarme, M and Blanco Valencia, X and Castro-Ospina, A E and Murillo Rendón, S and Peluffo-Ordóñez, D H},\\n doi = {10.29019/enfoqueute.v8n1.141},\\n journal = {Enfoque UTE},\\n number = {1}\\n}\",\"author_short\":[\"Viveros-Melo,  D.\",\"Ortega-Adarme,  M.\",\"Blanco Valencia,  X.\",\"Castro-Ospina,  A., E.\",\"Murillo Rendón,  S.\",\"Peluffo-Ordóñez,  D., H.\"],\"urls\":{\"Website\":\"https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/141\"},\"biburl\":\"https://bibbase.org/service/mendeley/dcbddeb4-43a7-32ca-8726-8f47f33c5362\",\"bibbaseid\":\"viverosmelo-ortegaadarme-blancovalencia-castroospina-murillorendn-peluffoordez-razonamientobasadoencasosaplicadoaldiagnsticomdicoutilizandoclasificadoresmulticlaseunestudiopreliminar-2017\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Kernel-based framework for spectral dimensionality reduction and clustering formulation: A theoretical study\",\"type\":\"article\",\"year\":\"2017\",\"pages\":\"31\",\"volume\":\"6\",\"websites\":\"http://revistas.usal.es/index.php/2255-2863/article/view/ADCAIJ2017613140\",\"id\":\"cc749f68-ecdc-31d3-9aa6-703c96831649\",\"created\":\"2021-02-10T05:25:39.021Z\",\"file_attached\":false,\"profile_id\":\"dcbddeb4-43a7-32ca-8726-8f47f33c5362\",\"last_modified\":\"2021-02-10T05:25:39.021Z\",\"read\":false,\"starred\":false,\"authored\":\"true\",\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"BLANCOVALENCIA2017\",\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"See, stats, and : https :// www. researchgate. net / publication/ 315475649 Kernel-based dimensionality formulation: A Article DOI : 10 . 14201 / ADCAIJ2017613140 CITATIONS 0 READS 57 6 , including : Some : DATA Case (CBR) for Xiomara Universidad 8 SEE Miguel Institución 35 SEE A . E . Castro - Ospina Instituto 26 SEE Diego Universidad 136 SEE All . The . KEYWORD ABSTRACT Kernel PCA ; Spectral clustering ; Support vector machine . This work outlines a unified formulation to represent spectral approaches for both dimensionality reduction and clustering . Proposed formulation starts with a generic latent variable model in terms of the projected input data matrix . Particularly , such a projection maps data onto a unknown high - dimensional space . Regarding this mod - el , a generalized optimization problem is stated using quadratic formulations and a least - squares support vector machine . The solution of the optimization is addressed through a primal - dual scheme . Once latent variables and parameters are determined , the resultant model outputs a versatile projected matrix able to represent data in a low - dimensional space , as well as to provide information about clusters . Particularly , proposed formulation yields solutions for kernel spectral clustering and weighted - ker - nel principal component analysis .\",\"bibtype\":\"article\",\"author\":\"BLANCO VALENCIA, Xiomara Patricia and BECERRA, M A and CASTRO OSPINA, A E and ORTEGA ADARME, M and VIVEROS MELO, D and PELUFFO ORDÓÑEZ, D H\",\"doi\":\"10.14201/ADCAIJ2017613140\",\"journal\":\"ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {Kernel-based framework for spectral dimensionality reduction and clustering formulation: A theoretical study},\\n type = {article},\\n year = {2017},\\n pages = {31},\\n volume = {6},\\n websites = {http://revistas.usal.es/index.php/2255-2863/article/view/ADCAIJ2017613140},\\n id = {cc749f68-ecdc-31d3-9aa6-703c96831649},\\n created = {2021-02-10T05:25:39.021Z},\\n file_attached = {false},\\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\\n last_modified = {2021-02-10T05:25:39.021Z},\\n read = {false},\\n starred = {false},\\n authored = {true},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {BLANCOVALENCIA2017},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {See, stats, and : https :// www. researchgate. net / publication/ 315475649 Kernel-based dimensionality formulation: A Article DOI : 10 . 14201 / ADCAIJ2017613140 CITATIONS 0 READS 57 6 , including : Some : DATA Case (CBR) for Xiomara Universidad 8 SEE Miguel Institución 35 SEE A . E . Castro - Ospina Instituto 26 SEE Diego Universidad 136 SEE All . The . KEYWORD ABSTRACT Kernel PCA ; Spectral clustering ; Support vector machine . This work outlines a unified formulation to represent spectral approaches for both dimensionality reduction and clustering . Proposed formulation starts with a generic latent variable model in terms of the projected input data matrix . Particularly , such a projection maps data onto a unknown high - dimensional space . Regarding this mod - el , a generalized optimization problem is stated using quadratic formulations and a least - squares support vector machine . The solution of the optimization is addressed through a primal - dual scheme . Once latent variables and parameters are determined , the resultant model outputs a versatile projected matrix able to represent data in a low - dimensional space , as well as to provide information about clusters . Particularly , proposed formulation yields solutions for kernel spectral clustering and weighted - ker - nel principal component analysis .},\\n bibtype = {article},\\n author = {BLANCO VALENCIA, Xiomara Patricia and BECERRA, M A and CASTRO OSPINA, A E and ORTEGA ADARME, M and VIVEROS MELO, D and PELUFFO ORDÓÑEZ, D H},\\n doi = {10.14201/ADCAIJ2017613140},\\n journal = {ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal},\\n number = {1}\\n}\",\"author_short\":[\"BLANCO VALENCIA,  X., P.\",\"BECERRA,  M., A.\",\"CASTRO OSPINA,  A., E.\",\"ORTEGA ADARME,  M.\",\"VIVEROS MELO,  D.\",\"PELUFFO ORDÓÑEZ,  D., H.\"],\"urls\":{\"Website\":\"http://revistas.usal.es/index.php/2255-2863/article/view/ADCAIJ2017613140\"},\"biburl\":\"https://bibbase.org/service/mendeley/dcbddeb4-43a7-32ca-8726-8f47f33c5362\",\"bibbaseid\":\"blancovalencia-becerra-castroospina-ortegaadarme-viverosmelo-peluffoordez-kernelbasedframeworkforspectraldimensionalityreductionandclusteringformulationatheoreticalstudy-2017\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"La Fundación Cardiovascular de Colombia a la vanguardia de la tecnología\",\"type\":\"article\",\"year\":\"2006\",\"keywords\":\"Diseases of the circulatory (Cardiovascular) syste,RC666-701,bioengineering,bioengineering specialities,bioingeniería,especialidades de la bioingeniería,new technologies,nuevas tecnologías\",\"websites\":\"http://www.scielo.org.co/pdf/rcca/v13n2/v13n2a5.pdf\",\"id\":\"3c1bf456-7f82-394d-a42a-2bac5a87348b\",\"created\":\"2021-02-10T05:25:39.048Z\",\"file_attached\":false,\"profile_id\":\"dcbddeb4-43a7-32ca-8726-8f47f33c5362\",\"last_modified\":\"2021-02-10T05:25:39.048Z\",\"read\":false,\"starred\":false,\"authored\":\"true\",\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Blanco2006\",\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Background: the Colombian Cardiovascular Foundation is aware of the importance of investing in research, development and innovation in order to incorporate and use scientific and technological advances that may contribute to the socio-economical development of the region and the country. Therefore, it has incremented its strategies to promote both a technological culture in our society, and the development of new local technologies or the adaptation of foreign ones to our needs. To achieve these goals, the Colombian Cardiovascular Foundation has created areas such as the strategic business unit FCV. Soft Software Factory, the bioengineering research group, the pediatric research unit and the unit of computer technology, that demand the integration of processes of technological development and the incorporation of new technologies to the regular clinical practice in a third complexity level institution. Objective: to describe the experience of the Colombian Cardiovascular Foundation in the integration of bioengineering and its specialties to the conventional clinical practice. Conclusions: the utilization of bioengineering in the conventional clinical practice favors institutional competitivity and motivates the improvement of the patients' quality of life, as it allows the creation of new tools to support the medical decisions in an efficient and timely way.\",\"bibtype\":\"article\",\"author\":\"Blanco, Xiomara and Gamboa, Wilson\",\"journal\":\"Revista Colombiana de Cardiologia\",\"bibtex\":\"@article{\\n title = {La Fundación Cardiovascular de Colombia a la vanguardia de la tecnología},\\n type = {article},\\n year = {2006},\\n keywords = {Diseases of the circulatory (Cardiovascular) syste,RC666-701,bioengineering,bioengineering specialities,bioingeniería,especialidades de la bioingeniería,new technologies,nuevas tecnologías},\\n websites = {http://www.scielo.org.co/pdf/rcca/v13n2/v13n2a5.pdf},\\n id = {3c1bf456-7f82-394d-a42a-2bac5a87348b},\\n created = {2021-02-10T05:25:39.048Z},\\n file_attached = {false},\\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\\n last_modified = {2021-02-10T05:25:39.048Z},\\n read = {false},\\n starred = {false},\\n authored = {true},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Blanco2006},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Background: the Colombian Cardiovascular Foundation is aware of the importance of investing in research, development and innovation in order to incorporate and use scientific and technological advances that may contribute to the socio-economical development of the region and the country. Therefore, it has incremented its strategies to promote both a technological culture in our society, and the development of new local technologies or the adaptation of foreign ones to our needs. To achieve these goals, the Colombian Cardiovascular Foundation has created areas such as the strategic business unit FCV. Soft Software Factory, the bioengineering research group, the pediatric research unit and the unit of computer technology, that demand the integration of processes of technological development and the incorporation of new technologies to the regular clinical practice in a third complexity level institution. Objective: to describe the experience of the Colombian Cardiovascular Foundation in the integration of bioengineering and its specialties to the conventional clinical practice. Conclusions: the utilization of bioengineering in the conventional clinical practice favors institutional competitivity and motivates the improvement of the patients' quality of life, as it allows the creation of new tools to support the medical decisions in an efficient and timely way.},\\n bibtype = {article},\\n author = {Blanco, Xiomara and Gamboa, Wilson},\\n journal = {Revista Colombiana de Cardiologia}\\n}\",\"author_short\":[\"Blanco,  X.\",\"Gamboa,  W.\"],\"urls\":{\"Website\":\"http://www.scielo.org.co/pdf/rcca/v13n2/v13n2a5.pdf\"},\"biburl\":\"https://bibbase.org/service/mendeley/dcbddeb4-43a7-32ca-8726-8f47f33c5362\",\"bibbaseid\":\"blanco-gamboa-lafundacincardiovasculardecolombiaalavanguardiadelatecnologa-2006\",\"role\":\"author\",\"keyword\":[\"Diseases of the circulatory (Cardiovascular) syste\",\"RC666-701\",\"bioengineering\",\"bioengineering specialities\",\"bioingeniería\",\"especialidades de la bioingeniería\",\"new technologies\",\"nuevas tecnologías\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Case based reasoning applied to medical diagnosis using multi-class classifier : A preliminary study\",\"type\":\"article\",\"year\":\"2017\",\"keywords\":\"Case based reasoning,High dimensionality,Variable selection\",\"websites\":\"https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/141\",\"id\":\"f84b9677-a988-3a31-bbb9-3588d5357dc9\",\"created\":\"2021-02-10T05:25:39.083Z\",\"file_attached\":false,\"profile_id\":\"dcbddeb4-43a7-32ca-8726-8f47f33c5362\",\"last_modified\":\"2021-02-10T05:25:39.083Z\",\"read\":false,\"starred\":false,\"authored\":\"true\",\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Viveros2017\",\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Case-based reasoning (CBR) is a process used for computer processing that tries to mimic the behavior of a human expert in making decisions regarding a subject and learn from the experience of past cases. CBR has demonstrated to be appropriate for working with unstructured domains data or difficult knowledge acquisition situations, such as medical diagnosis, where it is possible to identify diseases such as: cancer diagnosis, epilepsy prediction and appendicitis diagnosis. Some of the trends that may be developed for CBR in the health science are oriented to reduce the number of features in highly dimensional data. An important contribution may be the estimation of probabilities of belonging to each class for new cases. In this paper, in order to adequately represent the database and to avoid the inconveniences caused by the high dimensionality, noise and redundancy, a number of algorithms are used in the preprocessing stage for performing both variable selection and dimension reduction procedures. Also, a comparison of the performance of some representative multi-class classifiers is carried out to identify the most effective one to include within a CBR scheme. Particularly, four classification techniques and two reduction techniques are employed to make a comparative study of multi- class classifiers on CBR.\",\"bibtype\":\"article\",\"author\":\"Viveros, Diana and Ortega, Mabel and Blanco, Xiomara and Peluffo, Diego\",\"journal\":\"Enfoque UTE\",\"bibtex\":\"@article{\\n title = {Case based reasoning applied to medical diagnosis using multi-class classifier : A preliminary study},\\n type = {article},\\n year = {2017},\\n keywords = {Case based reasoning,High dimensionality,Variable selection},\\n websites = {https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/141},\\n id = {f84b9677-a988-3a31-bbb9-3588d5357dc9},\\n created = {2021-02-10T05:25:39.083Z},\\n file_attached = {false},\\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\\n last_modified = {2021-02-10T05:25:39.083Z},\\n read = {false},\\n starred = {false},\\n authored = {true},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Viveros2017},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Case-based reasoning (CBR) is a process used for computer processing that tries to mimic the behavior of a human expert in making decisions regarding a subject and learn from the experience of past cases. CBR has demonstrated to be appropriate for working with unstructured domains data or difficult knowledge acquisition situations, such as medical diagnosis, where it is possible to identify diseases such as: cancer diagnosis, epilepsy prediction and appendicitis diagnosis. Some of the trends that may be developed for CBR in the health science are oriented to reduce the number of features in highly dimensional data. An important contribution may be the estimation of probabilities of belonging to each class for new cases. In this paper, in order to adequately represent the database and to avoid the inconveniences caused by the high dimensionality, noise and redundancy, a number of algorithms are used in the preprocessing stage for performing both variable selection and dimension reduction procedures. Also, a comparison of the performance of some representative multi-class classifiers is carried out to identify the most effective one to include within a CBR scheme. Particularly, four classification techniques and two reduction techniques are employed to make a comparative study of multi- class classifiers on CBR.},\\n bibtype = {article},\\n author = {Viveros, Diana and Ortega, Mabel and Blanco, Xiomara and Peluffo, Diego},\\n journal = {Enfoque UTE}\\n}\",\"author_short\":[\"Viveros,  D.\",\"Ortega,  M.\",\"Blanco,  X.\",\"Peluffo,  D.\"],\"urls\":{\"Website\":\"https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/141\"},\"biburl\":\"https://bibbase.org/service/mendeley/dcbddeb4-43a7-32ca-8726-8f47f33c5362\",\"bibbaseid\":\"viveros-ortega-blanco-peluffo-casebasedreasoningappliedtomedicaldiagnosisusingmulticlassclassifierapreliminarystudy-2017\",\"role\":\"author\",\"keyword\":[\"Case based reasoning\",\"High dimensionality\",\"Variable selection\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Case-Based Reasoning applied to medical diagnosis and treatment\",\"type\":\"article\",\"year\":\"2013\",\"websites\":\"https://link.springer.com/chapter/10.1007/978-3-319-00551-5_17\",\"id\":\"600eb85a-b715-3d74-bb0a-cc66a6724ebe\",\"created\":\"2021-02-10T05:25:39.109Z\",\"file_attached\":false,\"profile_id\":\"dcbddeb4-43a7-32ca-8726-8f47f33c5362\",\"last_modified\":\"2021-02-10T05:25:39.109Z\",\"read\":false,\"starred\":false,\"authored\":\"true\",\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Blanco2013\",\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The Case-Based Reasoning (CBR) is an appropriate methodology to apply in diagnosis and treatment. Research in CBR is growing and there are shortcomings, especially in the adaptation mechanism. In this paper, besides presenting a methodological review of the technology applied to the diagnostics and health sector published in recent years, a new proposal is presented to improve the adaptation stage. This proposal is focused on preparing the data to create association rules that help to reduce the number of cases and facilitate learning adaptation rules. ©Springer International Publishing Switzerland 2013.\",\"bibtype\":\"article\",\"author\":\"Blanco, Xiomara and Rodríguez, Sara and Corchado, Juan M and Zato, Carolina\",\"doi\":\"10.1007/978-3-319-00551-5_17\",\"journal\":\"Advances in Intelligent Systems and Computing\",\"bibtex\":\"@article{\\n title = {Case-Based Reasoning applied to medical diagnosis and treatment},\\n type = {article},\\n year = {2013},\\n websites = {https://link.springer.com/chapter/10.1007/978-3-319-00551-5_17},\\n id = {600eb85a-b715-3d74-bb0a-cc66a6724ebe},\\n created = {2021-02-10T05:25:39.109Z},\\n file_attached = {false},\\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\\n last_modified = {2021-02-10T05:25:39.109Z},\\n read = {false},\\n starred = {false},\\n authored = {true},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Blanco2013},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The Case-Based Reasoning (CBR) is an appropriate methodology to apply in diagnosis and treatment. Research in CBR is growing and there are shortcomings, especially in the adaptation mechanism. In this paper, besides presenting a methodological review of the technology applied to the diagnostics and health sector published in recent years, a new proposal is presented to improve the adaptation stage. This proposal is focused on preparing the data to create association rules that help to reduce the number of cases and facilitate learning adaptation rules. ©Springer International Publishing Switzerland 2013.},\\n bibtype = {article},\\n author = {Blanco, Xiomara and Rodríguez, Sara and Corchado, Juan M and Zato, Carolina},\\n doi = {10.1007/978-3-319-00551-5_17},\\n journal = {Advances in Intelligent Systems and Computing}\\n}\",\"author_short\":[\"Blanco,  X.\",\"Rodríguez,  S.\",\"Corchado,  J., M.\",\"Zato,  C.\"],\"urls\":{\"Website\":\"https://link.springer.com/chapter/10.1007/978-3-319-00551-5_17\"},\"biburl\":\"https://bibbase.org/service/mendeley/dcbddeb4-43a7-32ca-8726-8f47f33c5362\",\"bibbaseid\":\"blanco-rodrguez-corchado-zato-casebasedreasoningappliedtomedicaldiagnosisandtreatment-2013\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"type\":\"inbook\",\"year\":\"2019\",\"keywords\":\"Forecasting,Genetic algorithm,Master Production Scheduling,Optimization,Production planning,Textile industry\",\"pages\":\"674-685\",\"websites\":\"http://link.springer.com/10.1007/978-3-030-29859-3_57\",\"id\":\"5850edf3-116d-3ffc-8cb2-a25165efa7b3\",\"created\":\"2021-02-10T05:25:39.114Z\",\"file_attached\":false,\"profile_id\":\"dcbddeb4-43a7-32ca-8726-8f47f33c5362\",\"last_modified\":\"2021-02-10T05:25:39.114Z\",\"read\":false,\"starred\":false,\"authored\":\"true\",\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Lorente-Leyva2019a\",\"private_publication\":false,\"abstract\":\"In a competitive environment, an industry’s success is directly related to the level of optimization of its processes, how production is planned and developed. In this area, the master production scheduling (MPS) is the key action for success. The object of study arises from the need to optimize the medium-term production planning system in a textile company, through genetic algorithms. This research begins with the analysis of the constraints, mainly determined by the installed capacity and the number of workers. The aggregate production planning is carried out for the T-shirts families. Due to such complexity, the application of bioinspired optimization techniques demonstrates their best performance, before industries that normally employ exact and simple methods that provide an empirical MPS but can compromise efficiency and costs. The products are then disaggregated for each of the items in which the MPS is determined, based on the analysis of the demand forecast, and the orders made by customers. From this, with the use of genetic algorithms, the MPS is optimized to carry out production planning, with an improvement of up to 96% of the level of service provided.\",\"bibtype\":\"inbook\",\"author\":\"Lorente-Leyva, Leandro L. and Murillo-Valle, Jefferson R. and Montero-Santos, Yakcleem and Herrera-Granda, Israel D. and Herrera-Granda, Erick P. and Rosero-Montalvo, Paul D. and Peluffo-Ordóñez, Diego H. and Blanco-Valencia, Xiomara P.\",\"doi\":\"10.1007/978-3-030-29859-3_57\",\"chapter\":\"Optimization of the Master Production Scheduling in a Textile Industry Using Genetic Algorithm\",\"title\":\"Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)\",\"bibtex\":\"@inbook{\\n type = {inbook},\\n year = {2019},\\n keywords = {Forecasting,Genetic algorithm,Master Production Scheduling,Optimization,Production planning,Textile industry},\\n pages = {674-685},\\n websites = {http://link.springer.com/10.1007/978-3-030-29859-3_57},\\n id = {5850edf3-116d-3ffc-8cb2-a25165efa7b3},\\n created = {2021-02-10T05:25:39.114Z},\\n file_attached = {false},\\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\\n last_modified = {2021-02-10T05:25:39.114Z},\\n read = {false},\\n starred = {false},\\n authored = {true},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Lorente-Leyva2019a},\\n private_publication = {false},\\n abstract = {In a competitive environment, an industry’s success is directly related to the level of optimization of its processes, how production is planned and developed. In this area, the master production scheduling (MPS) is the key action for success. The object of study arises from the need to optimize the medium-term production planning system in a textile company, through genetic algorithms. This research begins with the analysis of the constraints, mainly determined by the installed capacity and the number of workers. The aggregate production planning is carried out for the T-shirts families. Due to such complexity, the application of bioinspired optimization techniques demonstrates their best performance, before industries that normally employ exact and simple methods that provide an empirical MPS but can compromise efficiency and costs. The products are then disaggregated for each of the items in which the MPS is determined, based on the analysis of the demand forecast, and the orders made by customers. From this, with the use of genetic algorithms, the MPS is optimized to carry out production planning, with an improvement of up to 96% of the level of service provided.},\\n bibtype = {inbook},\\n author = {Lorente-Leyva, Leandro L. and Murillo-Valle, Jefferson R. and Montero-Santos, Yakcleem and Herrera-Granda, Israel D. and Herrera-Granda, Erick P. and Rosero-Montalvo, Paul D. and Peluffo-Ordóñez, Diego H. and Blanco-Valencia, Xiomara P.},\\n doi = {10.1007/978-3-030-29859-3_57},\\n chapter = {Optimization of the Master Production Scheduling in a Textile Industry Using Genetic Algorithm},\\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\\n}\",\"author_short\":[\"Lorente-Leyva,  L., L.\",\"Murillo-Valle,  J., R.\",\"Montero-Santos,  Y.\",\"Herrera-Granda,  I., D.\",\"Herrera-Granda,  E., P.\",\"Rosero-Montalvo,  P., D.\",\"Peluffo-Ordóñez,  D., H.\",\"Blanco-Valencia,  X., P.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/978-3-030-29859-3_57\"},\"biburl\":\"https://bibbase.org/service/mendeley/dcbddeb4-43a7-32ca-8726-8f47f33c5362\",\"bibbaseid\":\"lorenteleyva-murillovalle-monterosantos-herreragranda-herreragranda-roseromontalvo-peluffoordez-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019\",\"role\":\"author\",\"keyword\":[\"Forecasting\",\"Genetic algorithm\",\"Master Production Scheduling\",\"Optimization\",\"Production planning\",\"Textile industry\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"type\":\"inbook\",\"year\":\"2019\",\"keywords\":\"Data analysis,Environmental monitoring,Environmental science computing,Intelligent system\",\"pages\":\"686-696\",\"websites\":\"http://link.springer.com/10.1007/978-3-030-29859-3_58\",\"id\":\"d2e68c26-de41-3d77-bd1f-47914d2359d2\",\"created\":\"2021-02-10T05:25:39.155Z\",\"file_attached\":false,\"profile_id\":\"dcbddeb4-43a7-32ca-8726-8f47f33c5362\",\"last_modified\":\"2021-02-10T05:25:39.155Z\",\"read\":false,\"starred\":false,\"authored\":\"true\",\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Rosero-Montalvo2019c\",\"private_publication\":false,\"abstract\":\"This work presents a new approach to the Internet of Things (IoT) between sensor nodes and data analysis with visualization platform with the purpose to acquire urban pollution data. The main objective is to determine the degree of contamination in Ibarra city in real time. To do this, for one hand, thirteen IoT devices have been implemented. For another hand, a Prototype Selection and Data Balance algorithms comparison in relation to the classifier k-Nearest Neighbourhood is made. With this, the system has an adequate training set to achieve the highest classification performance. As a final result, the system presents a visualization platform that estimates the pollution condition with more than 90% accuracy.\",\"bibtype\":\"inbook\",\"author\":\"Rosero-Montalvo, Paul D. and López-Batista, Vivian F. and Peluffo-Ordóñez, Diego H. and Lorente-Leyva, Leandro L. and Blanco-Valencia, X. P.\",\"doi\":\"10.1007/978-3-030-29859-3_58\",\"chapter\":\"Urban Pollution Environmental Monitoring System Using IoT Devices and Data Visualization: A Case Study\",\"title\":\"Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)\",\"bibtex\":\"@inbook{\\n type = {inbook},\\n year = {2019},\\n keywords = {Data analysis,Environmental monitoring,Environmental science computing,Intelligent system},\\n pages = {686-696},\\n websites = {http://link.springer.com/10.1007/978-3-030-29859-3_58},\\n id = {d2e68c26-de41-3d77-bd1f-47914d2359d2},\\n created = {2021-02-10T05:25:39.155Z},\\n file_attached = {false},\\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\\n last_modified = {2021-02-10T05:25:39.155Z},\\n read = {false},\\n starred = {false},\\n authored = {true},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Rosero-Montalvo2019c},\\n private_publication = {false},\\n abstract = {This work presents a new approach to the Internet of Things (IoT) between sensor nodes and data analysis with visualization platform with the purpose to acquire urban pollution data. The main objective is to determine the degree of contamination in Ibarra city in real time. To do this, for one hand, thirteen IoT devices have been implemented. For another hand, a Prototype Selection and Data Balance algorithms comparison in relation to the classifier k-Nearest Neighbourhood is made. With this, the system has an adequate training set to achieve the highest classification performance. As a final result, the system presents a visualization platform that estimates the pollution condition with more than 90% accuracy.},\\n bibtype = {inbook},\\n author = {Rosero-Montalvo, Paul D. and López-Batista, Vivian F. and Peluffo-Ordóñez, Diego H. and Lorente-Leyva, Leandro L. and Blanco-Valencia, X. P.},\\n doi = {10.1007/978-3-030-29859-3_58},\\n chapter = {Urban Pollution Environmental Monitoring System Using IoT Devices and Data Visualization: A Case Study},\\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\\n}\",\"author_short\":[\"Rosero-Montalvo,  P., D.\",\"López-Batista,  V., F.\",\"Peluffo-Ordóñez,  D., H.\",\"Lorente-Leyva,  L., L.\",\"Blanco-Valencia,  X., P.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/978-3-030-29859-3_58\"},\"biburl\":\"https://bibbase.org/service/mendeley/dcbddeb4-43a7-32ca-8726-8f47f33c5362\",\"bibbaseid\":\"roseromontalvo-lpezbatista-peluffoordez-lorenteleyva-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019\",\"role\":\"author\",\"keyword\":[\"Data analysis\",\"Environmental monitoring\",\"Environmental science computing\",\"Intelligent system\"],\"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,@inbook{
 type = {inbook},
 year = {2018},
 keywords = {Biometric identification,Cardiac murmur,Electrocardiographic signal,Signal processing},
 pages = {410-418},
 websites = {http://link.springer.com/10.1007/978-3-030-03493-1_43},
 id = {0279fa9d-7b7e-3561-b8f8-18cbe6d222f1},
 created = {2021-02-10T05:25:38.895Z},
 file_attached = {false},
 profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},
 last_modified = {2021-02-10T05:25:38.895Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Becerra2018},
 private_publication = {false},
 abstract = {The process of distinguishing among human beings through the inspection of acquired data from physical or behavioral traits is known as biometric identification. Mostly, fingerprint- and iris-based biometric techniques are used. Nowadays, since such techniques are highly susceptible to be counterfeited, new biometric alternatives are explored mainly based on physiological signals and behavioral traits -which are useful not only for biometric identification purposes, but may also play a role as a vital signal indicator. In this connection, the electrocardiographic (ECG) signals have shown to be a suitable approach. Nonetheless, their informative components (morphology, rhythm, polarization, and among others) can be affected by the presence of a cardiac pathology. Even more, some other cardiac diseases cannot directly be detected by the ECG signal inspection but still have an effect on their waveform, that is the case of cardiac murmurs. Therefore, for biometric purposes, such signals should be analyzed submitted to the effects of pathologies. This paper presents a exploratory study aimed at assessing the influence of the presence of a pathology when analyzing ECG signals for implementing a biometric system. For experiments, a data base holding 20 healthy subjects and 20 pathological subjects (diagnosed with different types of cardiac murmurs) are considered. The proposed signal analysis consists of preprocessing, characterization (using wavelet features), feature selection and classification (five classifiers as well as a mixture of them are tested). As a result, through the performed comparison of the classification rates when testing pathological and normal ECG signals, the cardiac murmurs’ undesired effect on the identification mechanism performance is clearly unveiled.},
 bibtype = {inbook},
 author = {Becerra, M. A. and Duque-Mejía, C. and Zapata-Hernández, C. and Peluffo-Ordóñez, D. H. and Serna-Guarín, L. and Delgado-Trejos, Edilson and Revelo-Fuelagán, E. J. and Blanco Valencia, X. P.},
 doi = {10.1007/978-3-030-03493-1_43},
 chapter = {Exploratory Study of the Effects of Cardiac Murmurs on Electrocardiographic-Signal-Based Biometric Systems},
 title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}
}

@inbook{
 type = {inbook},
 year = {2018},
 keywords = {Dimensionality reduction,Generalized methodology,Kernel approximations,Low-computational cost,Multiple kernel learning,Spectral methods},
 pages = {661-669},
 websites = {http://link.springer.com/10.1007/978-3-030-03493-1_69},
 id = {64e2b849-aef0-35d8-861a-b2b29cf9315f},
 created = {2021-02-10T05:25:38.898Z},
 file_attached = {false},
 profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},
 last_modified = {2021-02-10T05:25:38.898Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Salazar-Castro2018},
 private_publication = {false},
 abstract = {Dimensionality reduction (DR) is a methodology used in many fields linked to data processing, and may represent a preprocessing stage or be an essential element for the representation and classification of data. The main objective of DR is to obtain a new representation of the original data in a space of smaller dimension, such that more refined information is produced, as well as the time of the subsequent processing is decreased and/or visual representations more intelligible for human beings are generated. The spectral DR methods involve the calculation of an eigenvalue and eigenvector decomposition, which is usually high-computational-cost demanding, and, therefore, the task of obtaining a more dynamic and interactive user-machine integration is difficult. Therefore, for the design of an interactive IV system based on DR spectral methods, it is necessary to propose a strategy to reduce the computational cost required in the calculation of eigenvectors and eigenvalues. For this purpose, it is proposed to use locally linear submatrices and spectral embedding. This allows integrating natural intelligence with computational intelligence for the representation of data interactively, dynamically and at low computational cost. Additionally, an interactive model is proposed that allows the user to dynamically visualize the data through a weighted mixture.},
 bibtype = {inbook},
 author = {Salazar-Castro, J. A. and Peña, D. F. and Basante, C. and Ortega, C. and Cruz-Cruz, L. and Revelo-Fuelagán, J. and Blanco-Valencia, X. P. and Castellanos-Domínguez, G. and Peluffo-Ordóñez, D. H.},
 doi = {10.1007/978-3-030-03493-1_69},
 chapter = {Generalized Low-Computational Cost Laplacian Eigenmaps},
 title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}
}

@inbook{
 type = {inbook},
 year = {2019},
 keywords = {Bayes,Case-based reasoning,Classification,Parametric,Probability},
 pages = {339-350},
 websites = {http://link.springer.com/10.1007/978-3-030-14799-0_29},
 id = {cb30131d-ab87-3ed0-b26f-4004b13ee7e6},
 created = {2021-02-10T05:25:38.975Z},
 file_attached = {false},
 profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},
 last_modified = {2021-02-10T05:25:38.975Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {BastidasTorres2019},
 private_publication = {false},
 abstract = {When searching for better solutions that improve the medical diagnosis accuracy, Case-Based reasoning systems (CBR) arise as a good option. This article seeks to improve these systems through the use of parametric and non-parametric probability estimation methods, particularly, at their recovery and adaptation stages. To this end, a set of experiments are conducted with two essentially different, medical databases (Cardiotocography and Cleveland databases), in order to find good parametric and non-parametric estimators. The results are remarkable as a high accuracy rate is achieved when using explored approaches: Naive Bayes and Nearest Neighbors (K-NN) estimators. In addition, a decrease on the involved processing time is reached, which suggests that proposed estimators incorporated into the recovery and adaptation stage becomes suitable for CBR systems, especially when dealing with support for medical diagnosis applications.},
 bibtype = {inbook},
 author = {Bastidas Torres, D. and Piñeros Rodriguez, C. and Peluffo-Ordóñez, Diego H. and Blanco Valencia, X. and Revelo-Fuelagán, Javier and Becerra, M. A. and Castro-Ospina, A. E. and Lorente-Leyva, Leandro L.},
 doi = {10.1007/978-3-030-14799-0_29},
 chapter = {Adaptation and Recovery Stages for Case-Based Reasoning Systems Using Bayesian Estimation and Density Estimation with Nearest Neighbors},
 title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}
}

@inbook{
 type = {inbook},
 year = {2016},
 keywords = {Dimensionality reduction,Generalized kernel formulation,Kernel PCA,Spectral clustering,Support vector machine},
 pages = {255-264},
 websites = {http://link.springer.com/10.1007/978-3-319-40162-1_28},
 id = {2f1f2725-75df-38fe-a220-32d52511547c},
 created = {2021-02-10T05:25:38.981Z},
 file_attached = {false},
 profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},
 last_modified = {2021-02-10T05:25:38.981Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Peluffo-Ordonez2016},
 source_type = {incollection},
 private_publication = {false},
 abstract = {This paper presents the development of a unified view of spectral clustering and unsupervised dimensionality reduction approaches within a generalized kernel framework. To do so, the authors propose a multipurpose latent variable model in terms of a high-dimensional representation of the input data matrix, which is incorporated into a least-squares support vector machine to yield a generalized optimization problem. After solving it via a primal-dual procedure, the final model results in a versatile projected matrix able to represent data in a low-dimensional space, as well as to provide information about clusters. Specifically, our formulation yields solutions for kernel spectral clustering and weighted-kernel principal component analysis.},
 bibtype = {inbook},
 author = {Peluffo-Ordóñez, D H and Becerra, M A and Castro-Ospina, A E and Blanco-Valencia, X and Alvarado-Pérez, J C and Therón, R and Anaya-Isaza, A},
 doi = {10.1007/978-3-319-40162-1_28},
 chapter = {On the Relationship Between Dimensionality Reduction and Spectral Clustering from a Kernel Viewpoint},
 title = {Advances in Intelligent Systems and Computing}
}

@inbook{
 type = {inbook},
 year = {2018},
 keywords = {Cascade classification,Case-based reasoning,Preprocessing,Probability},
 pages = {26-38},
 websites = {http://link.springer.com/10.1007/978-3-319-78723-7_3},
 id = {3351c72f-385f-3d27-b040-6be78e4e691d},
 created = {2021-02-10T05:25:38.984Z},
 file_attached = {false},
 profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},
 last_modified = {2021-02-10T05:25:38.984Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {BlancoValencia2018},
 private_publication = {false},
 abstract = {Case-Based Reasoning Systems (CBR) are in constant evolution, as a result, this article proposes improving the retrieve and adaption stages through a different approach. A series of experiments were made, divided in three sections: a proper pre-processing technique, a cascade classification, and a probability estimation procedure. Every stage offers an improvement, a better data representation, a more efficient classification, and a more precise probability estimation provided by a Support Vector Machine (SVM) estimator regarding more common approaches. Concluding, more complex techniques for classification and probability estimation are possible, improving CBR systems performance due to lower classification error in general cases.},
 bibtype = {inbook},
 author = {Blanco Valencia, X. and Bastidas Torres, D. and Piñeros Rodriguez, C. and Peluffo-Ordóñez, D. H. and Becerra, M. A. and Castro-Ospina, A. E.},
 doi = {10.1007/978-3-319-78723-7_3},
 chapter = {Case-Based Reasoning Systems for Medical Applications with Improved Adaptation and Recovery Stages},
 title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}
}

@article{
 title = {Razonamiento basado en casos aplicado al diagnóstico médico utilizando clasificadores multi-clase: Un estudio preliminar},
 type = {article},
 year = {2017},
 pages = {232-243},
 volume = {8},
 websites = {https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/141},
 month = {2},
 id = {1160d31c-9bc4-3569-b3e6-51a813010744},
 created = {2021-02-10T05:25:39.004Z},
 file_attached = {false},
 profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},
 last_modified = {2021-02-10T05:25:39.004Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Viveros-Melo2017},
 source_type = {article},
 private_publication = {false},
 abstract = {CBR ha demostrado ser apropiado para trabajar con datos de dominios poco estructurados o situaciones donde es difícil la adquisición de conocimiento, como es el caso del diagnóstico médico, donde es posible identificar enfermedades como: cáncer, predicción de epilepsia y diagnóstico de apendicitis. Algunas de las tendencias que se pueden desarrollar para CBR en la ciencia de la salud están orientadas a reducir el número de características en datos de gran dimensión. Una contribución importante puede ser la estimación de probabilidades de pertenencia a cada clase para los nuevos casos. Con el fin de representar adecuadamente la base de datos y evitar los inconvenientes causados por la alta dimensión, ruido y redundancia de los mimos, en este trabajo, se utiliza varios algoritmos en la etapa de pre-procesamiento para realizar una selección de variables y reducción de dimensiones. Además, se realiza una comparación del rendimiento de algunos clasificadores multi-clase representativos para identificar el más eficaz e incluirlo en un esquema CBR. En particular, se emplean cuatro técnicas de clasificación y dos técnicas de reducción para hacer un estudio comparativo de clasificadores multi-clase sobre CBR},
 bibtype = {article},
 author = {Viveros-Melo, D and Ortega-Adarme, M and Blanco Valencia, X and Castro-Ospina, A E and Murillo Rendón, S and Peluffo-Ordóñez, D H},
 doi = {10.29019/enfoqueute.v8n1.141},
 journal = {Enfoque UTE},
 number = {1}
}

@article{
 title = {Kernel-based framework for spectral dimensionality reduction and clustering formulation: A theoretical study},
 type = {article},
 year = {2017},
 pages = {31},
 volume = {6},
 websites = {http://revistas.usal.es/index.php/2255-2863/article/view/ADCAIJ2017613140},
 id = {cc749f68-ecdc-31d3-9aa6-703c96831649},
 created = {2021-02-10T05:25:39.021Z},
 file_attached = {false},
 profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},
 last_modified = {2021-02-10T05:25:39.021Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {BLANCOVALENCIA2017},
 source_type = {article},
 private_publication = {false},
 abstract = {See, stats, and : https :// www. researchgate. net / publication/ 315475649 Kernel-based dimensionality formulation: A Article DOI : 10 . 14201 / ADCAIJ2017613140 CITATIONS 0 READS 57 6 , including : Some : DATA Case (CBR) for Xiomara Universidad 8 SEE Miguel Institución 35 SEE A . E . Castro - Ospina Instituto 26 SEE Diego Universidad 136 SEE All . The . KEYWORD ABSTRACT Kernel PCA ; Spectral clustering ; Support vector machine . This work outlines a unified formulation to represent spectral approaches for both dimensionality reduction and clustering . Proposed formulation starts with a generic latent variable model in terms of the projected input data matrix . Particularly , such a projection maps data onto a unknown high - dimensional space . Regarding this mod - el , a generalized optimization problem is stated using quadratic formulations and a least - squares support vector machine . The solution of the optimization is addressed through a primal - dual scheme . Once latent variables and parameters are determined , the resultant model outputs a versatile projected matrix able to represent data in a low - dimensional space , as well as to provide information about clusters . Particularly , proposed formulation yields solutions for kernel spectral clustering and weighted - ker - nel principal component analysis .},
 bibtype = {article},
 author = {BLANCO VALENCIA, Xiomara Patricia and BECERRA, M A and CASTRO OSPINA, A E and ORTEGA ADARME, M and VIVEROS MELO, D and PELUFFO ORDÓÑEZ, D H},
 doi = {10.14201/ADCAIJ2017613140},
 journal = {ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal},
 number = {1}
}

@article{
 title = {La Fundación Cardiovascular de Colombia a la vanguardia de la tecnología},
 type = {article},
 year = {2006},
 keywords = {Diseases of the circulatory (Cardiovascular) syste,RC666-701,bioengineering,bioengineering specialities,bioingeniería,especialidades de la bioingeniería,new technologies,nuevas tecnologías},
 websites = {http://www.scielo.org.co/pdf/rcca/v13n2/v13n2a5.pdf},
 id = {3c1bf456-7f82-394d-a42a-2bac5a87348b},
 created = {2021-02-10T05:25:39.048Z},
 file_attached = {false},
 profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},
 last_modified = {2021-02-10T05:25:39.048Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Blanco2006},
 source_type = {article},
 private_publication = {false},
 abstract = {Background: the Colombian Cardiovascular Foundation is aware of the importance of investing in research, development and innovation in order to incorporate and use scientific and technological advances that may contribute to the socio-economical development of the region and the country. Therefore, it has incremented its strategies to promote both a technological culture in our society, and the development of new local technologies or the adaptation of foreign ones to our needs. To achieve these goals, the Colombian Cardiovascular Foundation has created areas such as the strategic business unit FCV. Soft Software Factory, the bioengineering research group, the pediatric research unit and the unit of computer technology, that demand the integration of processes of technological development and the incorporation of new technologies to the regular clinical practice in a third complexity level institution. Objective: to describe the experience of the Colombian Cardiovascular Foundation in the integration of bioengineering and its specialties to the conventional clinical practice. Conclusions: the utilization of bioengineering in the conventional clinical practice favors institutional competitivity and motivates the improvement of the patients' quality of life, as it allows the creation of new tools to support the medical decisions in an efficient and timely way.},
 bibtype = {article},
 author = {Blanco, Xiomara and Gamboa, Wilson},
 journal = {Revista Colombiana de Cardiologia}
}

@article{
 title = {Case based reasoning applied to medical diagnosis using multi-class classifier : A preliminary study},
 type = {article},
 year = {2017},
 keywords = {Case based reasoning,High dimensionality,Variable selection},
 websites = {https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/141},
 id = {f84b9677-a988-3a31-bbb9-3588d5357dc9},
 created = {2021-02-10T05:25:39.083Z},
 file_attached = {false},
 profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},
 last_modified = {2021-02-10T05:25:39.083Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Viveros2017},
 source_type = {article},
 private_publication = {false},
 abstract = {Case-based reasoning (CBR) is a process used for computer processing that tries to mimic the behavior of a human expert in making decisions regarding a subject and learn from the experience of past cases. CBR has demonstrated to be appropriate for working with unstructured domains data or difficult knowledge acquisition situations, such as medical diagnosis, where it is possible to identify diseases such as: cancer diagnosis, epilepsy prediction and appendicitis diagnosis. Some of the trends that may be developed for CBR in the health science are oriented to reduce the number of features in highly dimensional data. An important contribution may be the estimation of probabilities of belonging to each class for new cases. In this paper, in order to adequately represent the database and to avoid the inconveniences caused by the high dimensionality, noise and redundancy, a number of algorithms are used in the preprocessing stage for performing both variable selection and dimension reduction procedures. Also, a comparison of the performance of some representative multi-class classifiers is carried out to identify the most effective one to include within a CBR scheme. Particularly, four classification techniques and two reduction techniques are employed to make a comparative study of multi- class classifiers on CBR.},
 bibtype = {article},
 author = {Viveros, Diana and Ortega, Mabel and Blanco, Xiomara and Peluffo, Diego},
 journal = {Enfoque UTE}
}

@article{
 title = {Case-Based Reasoning applied to medical diagnosis and treatment},
 type = {article},
 year = {2013},
 websites = {https://link.springer.com/chapter/10.1007/978-3-319-00551-5_17},
 id = {600eb85a-b715-3d74-bb0a-cc66a6724ebe},
 created = {2021-02-10T05:25:39.109Z},
 file_attached = {false},
 profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},
 last_modified = {2021-02-10T05:25:39.109Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Blanco2013},
 source_type = {article},
 private_publication = {false},
 abstract = {The Case-Based Reasoning (CBR) is an appropriate methodology to apply in diagnosis and treatment. Research in CBR is growing and there are shortcomings, especially in the adaptation mechanism. In this paper, besides presenting a methodological review of the technology applied to the diagnostics and health sector published in recent years, a new proposal is presented to improve the adaptation stage. This proposal is focused on preparing the data to create association rules that help to reduce the number of cases and facilitate learning adaptation rules. ©Springer International Publishing Switzerland 2013.},
 bibtype = {article},
 author = {Blanco, Xiomara and Rodríguez, Sara and Corchado, Juan M and Zato, Carolina},
 doi = {10.1007/978-3-319-00551-5_17},
 journal = {Advances in Intelligent Systems and Computing}
}

@inbook{
 type = {inbook},
 year = {2019},
 keywords = {Forecasting,Genetic algorithm,Master Production Scheduling,Optimization,Production planning,Textile industry},
 pages = {674-685},
 websites = {http://link.springer.com/10.1007/978-3-030-29859-3_57},
 id = {5850edf3-116d-3ffc-8cb2-a25165efa7b3},
 created = {2021-02-10T05:25:39.114Z},
 file_attached = {false},
 profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},
 last_modified = {2021-02-10T05:25:39.114Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Lorente-Leyva2019a},
 private_publication = {false},
 abstract = {In a competitive environment, an industry’s success is directly related to the level of optimization of its processes, how production is planned and developed. In this area, the master production scheduling (MPS) is the key action for success. The object of study arises from the need to optimize the medium-term production planning system in a textile company, through genetic algorithms. This research begins with the analysis of the constraints, mainly determined by the installed capacity and the number of workers. The aggregate production planning is carried out for the T-shirts families. Due to such complexity, the application of bioinspired optimization techniques demonstrates their best performance, before industries that normally employ exact and simple methods that provide an empirical MPS but can compromise efficiency and costs. The products are then disaggregated for each of the items in which the MPS is determined, based on the analysis of the demand forecast, and the orders made by customers. From this, with the use of genetic algorithms, the MPS is optimized to carry out production planning, with an improvement of up to 96% of the level of service provided.},
 bibtype = {inbook},
 author = {Lorente-Leyva, Leandro L. and Murillo-Valle, Jefferson R. and Montero-Santos, Yakcleem and Herrera-Granda, Israel D. and Herrera-Granda, Erick P. and Rosero-Montalvo, Paul D. and Peluffo-Ordóñez, Diego H. and Blanco-Valencia, Xiomara P.},
 doi = {10.1007/978-3-030-29859-3_57},
 chapter = {Optimization of the Master Production Scheduling in a Textile Industry Using Genetic Algorithm},
 title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}
}

@inbook{
 type = {inbook},
 year = {2019},
 keywords = {Data analysis,Environmental monitoring,Environmental science computing,Intelligent system},
 pages = {686-696},
 websites = {http://link.springer.com/10.1007/978-3-030-29859-3_58},
 id = {d2e68c26-de41-3d77-bd1f-47914d2359d2},
 created = {2021-02-10T05:25:39.155Z},
 file_attached = {false},
 profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},
 last_modified = {2021-02-10T05:25:39.155Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Rosero-Montalvo2019c},
 private_publication = {false},
 abstract = {This work presents a new approach to the Internet of Things (IoT) between sensor nodes and data analysis with visualization platform with the purpose to acquire urban pollution data. The main objective is to determine the degree of contamination in Ibarra city in real time. To do this, for one hand, thirteen IoT devices have been implemented. For another hand, a Prototype Selection and Data Balance algorithms comparison in relation to the classifier k-Nearest Neighbourhood is made. With this, the system has an adequate training set to achieve the highest classification performance. As a final result, the system presents a visualization platform that estimates the pollution condition with more than 90% accuracy.},
 bibtype = {inbook},
 author = {Rosero-Montalvo, Paul D. and López-Batista, Vivian F. and Peluffo-Ordóñez, Diego H. and Lorente-Leyva, Leandro L. and Blanco-Valencia, X. P.},
 doi = {10.1007/978-3-030-29859-3_58},
 chapter = {Urban Pollution Environmental Monitoring System Using IoT Devices and Data Visualization: A Case Study},
 title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}
}\">\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! 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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_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        (3)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"bastidastorres-pierosrodriguez-peluffoordez-blancovalencia-revelofuelagn-becerra-castroospina-lorenteleyva-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/978-3-030-14799-0_29\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'bastidastorres-pierosrodriguez-peluffoordez-blancovalencia-revelofuelagn-becerra-castroospina-lorenteleyva-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019', 'http://link.springer.com/10.1007/978-3-030-14799-0_29', event);\">\n    Adaptation and Recovery Stages for Case-Based Reasoning Systems Using Bayesian Estimation and Density Estimation with Nearest Neighbors.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Bastidas Torres,  D.; Piñeros Rodriguez,  C.; Peluffo-Ordóñez,  D., H.; Blanco Valencia,  X.; Revelo-Fuelagán,  J.; Becerra,  M., A.; Castro-Ospina,  A., E.;  and Lorente-Leyva,  L., L.\n</span>\n\n  \n\n</span>\n\n  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 339-350.  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://link.springer.com/10.1007/978-3-030-14799-0_29\"\n     onclick=\"log_download('bastidastorres-pierosrodriguez-peluffoordez-blancovalencia-revelofuelagn-becerra-castroospina-lorenteleyva-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019', 'http://link.springer.com/10.1007/978-3-030-14799-0_29', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) [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/10.1007/978-3-030-14799-0_29\"\n     onclick=\"log_download('bastidastorres-pierosrodriguez-peluffoordez-blancovalencia-revelofuelagn-becerra-castroospina-lorenteleyva-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019', 'http://doi.org/10.1007/978-3-030-14799-0_29', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bastidastorres-pierosrodriguez-peluffoordez-blancovalencia-revelofuelagn-becerra-castroospina-lorenteleyva-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-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('bastidastorres-pierosrodriguez-peluffoordez-blancovalencia-revelofuelagn-becerra-castroospina-lorenteleyva-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-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  \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;\">@inbook{\n type = {inbook},\n year = {2019},\n keywords = {Bayes,Case-based reasoning,Classification,Parametric,Probability},\n pages = {339-350},\n websites = {http://link.springer.com/10.1007/978-3-030-14799-0_29},\n id = {cb30131d-ab87-3ed0-b26f-4004b13ee7e6},\n created = {2021-02-10T05:25:38.975Z},\n file_attached = {false},\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\n last_modified = {2021-02-10T05:25:38.975Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {true},\n hidden = {false},\n citation_key = {BastidasTorres2019},\n private_publication = {false},\n abstract = {When searching for better solutions that improve the medical diagnosis accuracy, Case-Based reasoning systems (CBR) arise as a good option. This article seeks to improve these systems through the use of parametric and non-parametric probability estimation methods, particularly, at their recovery and adaptation stages. To this end, a set of experiments are conducted with two essentially different, medical databases (Cardiotocography and Cleveland databases), in order to find good parametric and non-parametric estimators. The results are remarkable as a high accuracy rate is achieved when using explored approaches: Naive Bayes and Nearest Neighbors (K-NN) estimators. In addition, a decrease on the involved processing time is reached, which suggests that proposed estimators incorporated into the recovery and adaptation stage becomes suitable for CBR systems, especially when dealing with support for medical diagnosis applications.},\n bibtype = {inbook},\n author = {Bastidas Torres, D. and Piñeros Rodriguez, C. and Peluffo-Ordóñez, Diego H. and Blanco Valencia, X. and Revelo-Fuelagán, Javier and Becerra, M. A. and Castro-Ospina, A. E. and Lorente-Leyva, Leandro L.},\n doi = {10.1007/978-3-030-14799-0_29},\n chapter = {Adaptation and Recovery Stages for Case-Based Reasoning Systems Using Bayesian Estimation and Density Estimation with Nearest Neighbors},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  When searching for better solutions that improve the medical diagnosis accuracy, Case-Based reasoning systems (CBR) arise as a good option. This article seeks to improve these systems through the use of parametric and non-parametric probability estimation methods, particularly, at their recovery and adaptation stages. To this end, a set of experiments are conducted with two essentially different, medical databases (Cardiotocography and Cleveland databases), in order to find good parametric and non-parametric estimators. The results are remarkable as a high accuracy rate is achieved when using explored approaches: Naive Bayes and Nearest Neighbors (K-NN) estimators. In addition, a decrease on the involved processing time is reached, which suggests that proposed estimators incorporated into the recovery and adaptation stage becomes suitable for CBR systems, especially when dealing with support for medical diagnosis applications.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"lorenteleyva-murillovalle-monterosantos-herreragranda-herreragranda-roseromontalvo-peluffoordez-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/978-3-030-29859-3_57\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'lorenteleyva-murillovalle-monterosantos-herreragranda-herreragranda-roseromontalvo-peluffoordez-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019', 'http://link.springer.com/10.1007/978-3-030-29859-3_57', event);\">\n    Optimization of the Master Production Scheduling in a Textile Industry Using Genetic Algorithm.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lorente-Leyva,  L., L.; Murillo-Valle,  J., R.; Montero-Santos,  Y.; Herrera-Granda,  I., D.; Herrera-Granda,  E., P.; Rosero-Montalvo,  P., D.; Peluffo-Ordóñez,  D., H.;  and Blanco-Valencia,  X., P.\n</span>\n\n  \n\n</span>\n\n  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 674-685.  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://link.springer.com/10.1007/978-3-030-29859-3_57\"\n     onclick=\"log_download('lorenteleyva-murillovalle-monterosantos-herreragranda-herreragranda-roseromontalvo-peluffoordez-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019', 'http://link.springer.com/10.1007/978-3-030-29859-3_57', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) [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/10.1007/978-3-030-29859-3_57\"\n     onclick=\"log_download('lorenteleyva-murillovalle-monterosantos-herreragranda-herreragranda-roseromontalvo-peluffoordez-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019', 'http://doi.org/10.1007/978-3-030-29859-3_57', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lorenteleyva-murillovalle-monterosantos-herreragranda-herreragranda-roseromontalvo-peluffoordez-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-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('lorenteleyva-murillovalle-monterosantos-herreragranda-herreragranda-roseromontalvo-peluffoordez-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-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  \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;\">@inbook{\n type = {inbook},\n year = {2019},\n keywords = {Forecasting,Genetic algorithm,Master Production Scheduling,Optimization,Production planning,Textile industry},\n pages = {674-685},\n websites = {http://link.springer.com/10.1007/978-3-030-29859-3_57},\n id = {5850edf3-116d-3ffc-8cb2-a25165efa7b3},\n created = {2021-02-10T05:25:39.114Z},\n file_attached = {false},\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\n last_modified = {2021-02-10T05:25:39.114Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {true},\n hidden = {false},\n citation_key = {Lorente-Leyva2019a},\n private_publication = {false},\n abstract = {In a competitive environment, an industry’s success is directly related to the level of optimization of its processes, how production is planned and developed. In this area, the master production scheduling (MPS) is the key action for success. The object of study arises from the need to optimize the medium-term production planning system in a textile company, through genetic algorithms. This research begins with the analysis of the constraints, mainly determined by the installed capacity and the number of workers. The aggregate production planning is carried out for the T-shirts families. Due to such complexity, the application of bioinspired optimization techniques demonstrates their best performance, before industries that normally employ exact and simple methods that provide an empirical MPS but can compromise efficiency and costs. The products are then disaggregated for each of the items in which the MPS is determined, based on the analysis of the demand forecast, and the orders made by customers. From this, with the use of genetic algorithms, the MPS is optimized to carry out production planning, with an improvement of up to 96% of the level of service provided.},\n bibtype = {inbook},\n author = {Lorente-Leyva, Leandro L. and Murillo-Valle, Jefferson R. and Montero-Santos, Yakcleem and Herrera-Granda, Israel D. and Herrera-Granda, Erick P. and Rosero-Montalvo, Paul D. and Peluffo-Ordóñez, Diego H. and Blanco-Valencia, Xiomara P.},\n doi = {10.1007/978-3-030-29859-3_57},\n chapter = {Optimization of the Master Production Scheduling in a Textile Industry Using Genetic Algorithm},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In a competitive environment, an industry’s success is directly related to the level of optimization of its processes, how production is planned and developed. In this area, the master production scheduling (MPS) is the key action for success. The object of study arises from the need to optimize the medium-term production planning system in a textile company, through genetic algorithms. This research begins with the analysis of the constraints, mainly determined by the installed capacity and the number of workers. The aggregate production planning is carried out for the T-shirts families. Due to such complexity, the application of bioinspired optimization techniques demonstrates their best performance, before industries that normally employ exact and simple methods that provide an empirical MPS but can compromise efficiency and costs. The products are then disaggregated for each of the items in which the MPS is determined, based on the analysis of the demand forecast, and the orders made by customers. From this, with the use of genetic algorithms, the MPS is optimized to carry out production planning, with an improvement of up to 96% of the level of service provided.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"roseromontalvo-lpezbatista-peluffoordez-lorenteleyva-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/978-3-030-29859-3_58\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'roseromontalvo-lpezbatista-peluffoordez-lorenteleyva-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019', 'http://link.springer.com/10.1007/978-3-030-29859-3_58', event);\">\n    Urban Pollution Environmental Monitoring System Using IoT Devices and Data Visualization: A Case Study.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Rosero-Montalvo,  P., D.; López-Batista,  V., F.; Peluffo-Ordóñez,  D., H.; Lorente-Leyva,  L., L.;  and Blanco-Valencia,  X., P.\n</span>\n\n  \n\n</span>\n\n  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 686-696.  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://link.springer.com/10.1007/978-3-030-29859-3_58\"\n     onclick=\"log_download('roseromontalvo-lpezbatista-peluffoordez-lorenteleyva-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019', 'http://link.springer.com/10.1007/978-3-030-29859-3_58', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) [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/10.1007/978-3-030-29859-3_58\"\n     onclick=\"log_download('roseromontalvo-lpezbatista-peluffoordez-lorenteleyva-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019', 'http://doi.org/10.1007/978-3-030-29859-3_58', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/roseromontalvo-lpezbatista-peluffoordez-lorenteleyva-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-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('roseromontalvo-lpezbatista-peluffoordez-lorenteleyva-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-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  \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;\">@inbook{\n type = {inbook},\n year = {2019},\n keywords = {Data analysis,Environmental monitoring,Environmental science computing,Intelligent system},\n pages = {686-696},\n websites = {http://link.springer.com/10.1007/978-3-030-29859-3_58},\n id = {d2e68c26-de41-3d77-bd1f-47914d2359d2},\n created = {2021-02-10T05:25:39.155Z},\n file_attached = {false},\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\n last_modified = {2021-02-10T05:25:39.155Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2019c},\n private_publication = {false},\n abstract = {This work presents a new approach to the Internet of Things (IoT) between sensor nodes and data analysis with visualization platform with the purpose to acquire urban pollution data. The main objective is to determine the degree of contamination in Ibarra city in real time. To do this, for one hand, thirteen IoT devices have been implemented. For another hand, a Prototype Selection and Data Balance algorithms comparison in relation to the classifier k-Nearest Neighbourhood is made. With this, the system has an adequate training set to achieve the highest classification performance. As a final result, the system presents a visualization platform that estimates the pollution condition with more than 90% accuracy.},\n bibtype = {inbook},\n author = {Rosero-Montalvo, Paul D. and López-Batista, Vivian F. and Peluffo-Ordóñez, Diego H. and Lorente-Leyva, Leandro L. and Blanco-Valencia, X. P.},\n doi = {10.1007/978-3-030-29859-3_58},\n chapter = {Urban Pollution Environmental Monitoring System Using IoT Devices and Data Visualization: A Case Study},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This work presents a new approach to the Internet of Things (IoT) between sensor nodes and data analysis with visualization platform with the purpose to acquire urban pollution data. The main objective is to determine the degree of contamination in Ibarra city in real time. To do this, for one hand, thirteen IoT devices have been implemented. For another hand, a Prototype Selection and Data Balance algorithms comparison in relation to the classifier k-Nearest Neighbourhood is made. With this, the system has an adequate training set to achieve the highest classification performance. As a final result, the system presents a visualization platform that estimates the pollution condition with more than 90% accuracy.\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        (3)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"becerra-duquemeja-zapatahernndez-peluffoordez-sernaguarn-delgadotrejos-revelofuelagn-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/978-3-030-03493-1_43\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'becerra-duquemeja-zapatahernndez-peluffoordez-sernaguarn-delgadotrejos-revelofuelagn-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2018', 'http://link.springer.com/10.1007/978-3-030-03493-1_43', event);\">\n    Exploratory Study of the Effects of Cardiac Murmurs on Electrocardiographic-Signal-Based Biometric Systems.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Becerra,  M., A.; Duque-Mejía,  C.; Zapata-Hernández,  C.; Peluffo-Ordóñez,  D., H.; Serna-Guarín,  L.; Delgado-Trejos,  E.; Revelo-Fuelagán,  E., J.;  and Blanco Valencia,  X., P.\n</span>\n\n  \n\n</span>\n\n  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 410-418.  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://link.springer.com/10.1007/978-3-030-03493-1_43\"\n     onclick=\"log_download('becerra-duquemeja-zapatahernndez-peluffoordez-sernaguarn-delgadotrejos-revelofuelagn-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2018', 'http://link.springer.com/10.1007/978-3-030-03493-1_43', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) [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/10.1007/978-3-030-03493-1_43\"\n     onclick=\"log_download('becerra-duquemeja-zapatahernndez-peluffoordez-sernaguarn-delgadotrejos-revelofuelagn-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2018', 'http://doi.org/10.1007/978-3-030-03493-1_43', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/becerra-duquemeja-zapatahernndez-peluffoordez-sernaguarn-delgadotrejos-revelofuelagn-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-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('becerra-duquemeja-zapatahernndez-peluffoordez-sernaguarn-delgadotrejos-revelofuelagn-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-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  \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 = {2018},\n keywords = {Biometric identification,Cardiac murmur,Electrocardiographic signal,Signal processing},\n pages = {410-418},\n websites = {http://link.springer.com/10.1007/978-3-030-03493-1_43},\n id = {0279fa9d-7b7e-3561-b8f8-18cbe6d222f1},\n created = {2021-02-10T05:25:38.895Z},\n file_attached = {false},\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\n last_modified = {2021-02-10T05:25:38.895Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {true},\n hidden = {false},\n citation_key = {Becerra2018},\n private_publication = {false},\n abstract = {The process of distinguishing among human beings through the inspection of acquired data from physical or behavioral traits is known as biometric identification. Mostly, fingerprint- and iris-based biometric techniques are used. Nowadays, since such techniques are highly susceptible to be counterfeited, new biometric alternatives are explored mainly based on physiological signals and behavioral traits -which are useful not only for biometric identification purposes, but may also play a role as a vital signal indicator. In this connection, the electrocardiographic (ECG) signals have shown to be a suitable approach. Nonetheless, their informative components (morphology, rhythm, polarization, and among others) can be affected by the presence of a cardiac pathology. Even more, some other cardiac diseases cannot directly be detected by the ECG signal inspection but still have an effect on their waveform, that is the case of cardiac murmurs. Therefore, for biometric purposes, such signals should be analyzed submitted to the effects of pathologies. This paper presents a exploratory study aimed at assessing the influence of the presence of a pathology when analyzing ECG signals for implementing a biometric system. For experiments, a data base holding 20 healthy subjects and 20 pathological subjects (diagnosed with different types of cardiac murmurs) are considered. The proposed signal analysis consists of preprocessing, characterization (using wavelet features), feature selection and classification (five classifiers as well as a mixture of them are tested). As a result, through the performed comparison of the classification rates when testing pathological and normal ECG signals, the cardiac murmurs’ undesired effect on the identification mechanism performance is clearly unveiled.},\n bibtype = {inbook},\n author = {Becerra, M. A. and Duque-Mejía, C. and Zapata-Hernández, C. and Peluffo-Ordóñez, D. H. and Serna-Guarín, L. and Delgado-Trejos, Edilson and Revelo-Fuelagán, E. J. and Blanco Valencia, X. P.},\n doi = {10.1007/978-3-030-03493-1_43},\n chapter = {Exploratory Study of the Effects of Cardiac Murmurs on Electrocardiographic-Signal-Based Biometric Systems},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The process of distinguishing among human beings through the inspection of acquired data from physical or behavioral traits is known as biometric identification. Mostly, fingerprint- and iris-based biometric techniques are used. Nowadays, since such techniques are highly susceptible to be counterfeited, new biometric alternatives are explored mainly based on physiological signals and behavioral traits -which are useful not only for biometric identification purposes, but may also play a role as a vital signal indicator. In this connection, the electrocardiographic (ECG) signals have shown to be a suitable approach. Nonetheless, their informative components (morphology, rhythm, polarization, and among others) can be affected by the presence of a cardiac pathology. Even more, some other cardiac diseases cannot directly be detected by the ECG signal inspection but still have an effect on their waveform, that is the case of cardiac murmurs. Therefore, for biometric purposes, such signals should be analyzed submitted to the effects of pathologies. This paper presents a exploratory study aimed at assessing the influence of the presence of a pathology when analyzing ECG signals for implementing a biometric system. For experiments, a data base holding 20 healthy subjects and 20 pathological subjects (diagnosed with different types of cardiac murmurs) are considered. The proposed signal analysis consists of preprocessing, characterization (using wavelet features), feature selection and classification (five classifiers as well as a mixture of them are tested). As a result, through the performed comparison of the classification rates when testing pathological and normal ECG signals, the cardiac murmurs’ undesired effect on the identification mechanism performance is clearly unveiled.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"salazarcastro-pea-basante-ortega-cruzcruz-revelofuelagn-blancovalencia-castellanosdomnguez-etal-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/978-3-030-03493-1_69\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'salazarcastro-pea-basante-ortega-cruzcruz-revelofuelagn-blancovalencia-castellanosdomnguez-etal-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2018', 'http://link.springer.com/10.1007/978-3-030-03493-1_69', event);\">\n    Generalized Low-Computational Cost Laplacian Eigenmaps.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Salazar-Castro,  J., A.; Peña,  D., F.; Basante,  C.; Ortega,  C.; Cruz-Cruz,  L.; Revelo-Fuelagán,  J.; Blanco-Valencia,  X., P.; Castellanos-Domínguez,  G.;  and Peluffo-Ordóñez,  D., H.\n</span>\n\n  \n\n</span>\n\n  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 661-669.  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://link.springer.com/10.1007/978-3-030-03493-1_69\"\n     onclick=\"log_download('salazarcastro-pea-basante-ortega-cruzcruz-revelofuelagn-blancovalencia-castellanosdomnguez-etal-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2018', 'http://link.springer.com/10.1007/978-3-030-03493-1_69', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) [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/10.1007/978-3-030-03493-1_69\"\n     onclick=\"log_download('salazarcastro-pea-basante-ortega-cruzcruz-revelofuelagn-blancovalencia-castellanosdomnguez-etal-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2018', 'http://doi.org/10.1007/978-3-030-03493-1_69', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/salazarcastro-pea-basante-ortega-cruzcruz-revelofuelagn-blancovalencia-castellanosdomnguez-etal-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-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  &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('salazarcastro-pea-basante-ortega-cruzcruz-revelofuelagn-blancovalencia-castellanosdomnguez-etal-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-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  \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;\">@inbook{\n type = {inbook},\n year = {2018},\n keywords = {Dimensionality reduction,Generalized methodology,Kernel approximations,Low-computational cost,Multiple kernel learning,Spectral methods},\n pages = {661-669},\n websites = {http://link.springer.com/10.1007/978-3-030-03493-1_69},\n id = {64e2b849-aef0-35d8-861a-b2b29cf9315f},\n created = {2021-02-10T05:25:38.898Z},\n file_attached = {false},\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\n last_modified = {2021-02-10T05:25:38.898Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {true},\n hidden = {false},\n citation_key = {Salazar-Castro2018},\n private_publication = {false},\n abstract = {Dimensionality reduction (DR) is a methodology used in many fields linked to data processing, and may represent a preprocessing stage or be an essential element for the representation and classification of data. The main objective of DR is to obtain a new representation of the original data in a space of smaller dimension, such that more refined information is produced, as well as the time of the subsequent processing is decreased and/or visual representations more intelligible for human beings are generated. The spectral DR methods involve the calculation of an eigenvalue and eigenvector decomposition, which is usually high-computational-cost demanding, and, therefore, the task of obtaining a more dynamic and interactive user-machine integration is difficult. Therefore, for the design of an interactive IV system based on DR spectral methods, it is necessary to propose a strategy to reduce the computational cost required in the calculation of eigenvectors and eigenvalues. For this purpose, it is proposed to use locally linear submatrices and spectral embedding. This allows integrating natural intelligence with computational intelligence for the representation of data interactively, dynamically and at low computational cost. Additionally, an interactive model is proposed that allows the user to dynamically visualize the data through a weighted mixture.},\n bibtype = {inbook},\n author = {Salazar-Castro, J. A. and Peña, D. F. and Basante, C. and Ortega, C. and Cruz-Cruz, L. and Revelo-Fuelagán, J. and Blanco-Valencia, X. P. and Castellanos-Domínguez, G. and Peluffo-Ordóñez, D. H.},\n doi = {10.1007/978-3-030-03493-1_69},\n chapter = {Generalized Low-Computational Cost Laplacian Eigenmaps},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Dimensionality reduction (DR) is a methodology used in many fields linked to data processing, and may represent a preprocessing stage or be an essential element for the representation and classification of data. The main objective of DR is to obtain a new representation of the original data in a space of smaller dimension, such that more refined information is produced, as well as the time of the subsequent processing is decreased and/or visual representations more intelligible for human beings are generated. The spectral DR methods involve the calculation of an eigenvalue and eigenvector decomposition, which is usually high-computational-cost demanding, and, therefore, the task of obtaining a more dynamic and interactive user-machine integration is difficult. Therefore, for the design of an interactive IV system based on DR spectral methods, it is necessary to propose a strategy to reduce the computational cost required in the calculation of eigenvectors and eigenvalues. For this purpose, it is proposed to use locally linear submatrices and spectral embedding. This allows integrating natural intelligence with computational intelligence for the representation of data interactively, dynamically and at low computational cost. Additionally, an interactive model is proposed that allows the user to dynamically visualize the data through a weighted mixture.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"blancovalencia-bastidastorres-pierosrodriguez-peluffoordez-becerra-castroospina-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/978-3-319-78723-7_3\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'blancovalencia-bastidastorres-pierosrodriguez-peluffoordez-becerra-castroospina-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2018', 'http://link.springer.com/10.1007/978-3-319-78723-7_3', event);\">\n    Case-Based Reasoning Systems for Medical Applications with Improved Adaptation and Recovery Stages.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Blanco Valencia,  X.; Bastidas Torres,  D.; Piñeros Rodriguez,  C.; Peluffo-Ordóñez,  D., H.; Becerra,  M., A.;  and Castro-Ospina,  A., E.\n</span>\n\n  \n\n</span>\n\n  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 26-38.  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://link.springer.com/10.1007/978-3-319-78723-7_3\"\n     onclick=\"log_download('blancovalencia-bastidastorres-pierosrodriguez-peluffoordez-becerra-castroospina-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2018', 'http://link.springer.com/10.1007/978-3-319-78723-7_3', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) [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/10.1007/978-3-319-78723-7_3\"\n     onclick=\"log_download('blancovalencia-bastidastorres-pierosrodriguez-peluffoordez-becerra-castroospina-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2018', 'http://doi.org/10.1007/978-3-319-78723-7_3', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/blancovalencia-bastidastorres-pierosrodriguez-peluffoordez-becerra-castroospina-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-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('blancovalencia-bastidastorres-pierosrodriguez-peluffoordez-becerra-castroospina-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-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  \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 = {2018},\n keywords = {Cascade classification,Case-based reasoning,Preprocessing,Probability},\n pages = {26-38},\n websites = {http://link.springer.com/10.1007/978-3-319-78723-7_3},\n id = {3351c72f-385f-3d27-b040-6be78e4e691d},\n created = {2021-02-10T05:25:38.984Z},\n file_attached = {false},\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\n last_modified = {2021-02-10T05:25:38.984Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {true},\n hidden = {false},\n citation_key = {BlancoValencia2018},\n private_publication = {false},\n abstract = {Case-Based Reasoning Systems (CBR) are in constant evolution, as a result, this article proposes improving the retrieve and adaption stages through a different approach. A series of experiments were made, divided in three sections: a proper pre-processing technique, a cascade classification, and a probability estimation procedure. Every stage offers an improvement, a better data representation, a more efficient classification, and a more precise probability estimation provided by a Support Vector Machine (SVM) estimator regarding more common approaches. Concluding, more complex techniques for classification and probability estimation are possible, improving CBR systems performance due to lower classification error in general cases.},\n bibtype = {inbook},\n author = {Blanco Valencia, X. and Bastidas Torres, D. and Piñeros Rodriguez, C. and Peluffo-Ordóñez, D. H. and Becerra, M. A. and Castro-Ospina, A. E.},\n doi = {10.1007/978-3-319-78723-7_3},\n chapter = {Case-Based Reasoning Systems for Medical Applications with Improved Adaptation and Recovery Stages},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Case-Based Reasoning Systems (CBR) are in constant evolution, as a result, this article proposes improving the retrieve and adaption stages through a different approach. A series of experiments were made, divided in three sections: a proper pre-processing technique, a cascade classification, and a probability estimation procedure. Every stage offers an improvement, a better data representation, a more efficient classification, and a more precise probability estimation provided by a Support Vector Machine (SVM) estimator regarding more common approaches. Concluding, more complex techniques for classification and probability estimation are possible, improving CBR systems performance due to lower classification error in general cases.\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        (3)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"viverosmelo-ortegaadarme-blancovalencia-castroospina-murillorendn-peluffoordez-razonamientobasadoencasosaplicadoaldiagnsticomdicoutilizandoclasificadoresmulticlaseunestudiopreliminar-2017\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/141\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'viverosmelo-ortegaadarme-blancovalencia-castroospina-murillorendn-peluffoordez-razonamientobasadoencasosaplicadoaldiagnsticomdicoutilizandoclasificadoresmulticlaseunestudiopreliminar-2017', 'https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/141', event);\">\n    Razonamiento basado en casos aplicado al diagnóstico médico utilizando clasificadores multi-clase: Un estudio preliminar.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Viveros-Melo,  D.; Ortega-Adarme,  M.; Blanco Valencia,  X.; Castro-Ospina,  A., E.; Murillo Rendón,  S.;  and Peluffo-Ordóñez,  D., H.\n</span>\n\n  \n\n</span>\n\n  <i>Enfoque UTE</i>, 8(1): 232-243. 2 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=\"https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/141\"\n     onclick=\"log_download('viverosmelo-ortegaadarme-blancovalencia-castroospina-murillorendn-peluffoordez-razonamientobasadoencasosaplicadoaldiagnsticomdicoutilizandoclasificadoresmulticlaseunestudiopreliminar-2017', 'https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/141', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Razonamiento basado en casos aplicado al diagnóstico médico utilizando clasificadores multi-clase: Un estudio preliminar [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/10.29019/enfoqueute.v8n1.141\"\n     onclick=\"log_download('viverosmelo-ortegaadarme-blancovalencia-castroospina-murillorendn-peluffoordez-razonamientobasadoencasosaplicadoaldiagnsticomdicoutilizandoclasificadoresmulticlaseunestudiopreliminar-2017', 'http://doi.org/10.29019/enfoqueute.v8n1.141', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/viverosmelo-ortegaadarme-blancovalencia-castroospina-murillorendn-peluffoordez-razonamientobasadoencasosaplicadoaldiagnsticomdicoutilizandoclasificadoresmulticlaseunestudiopreliminar-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('viverosmelo-ortegaadarme-blancovalencia-castroospina-murillorendn-peluffoordez-razonamientobasadoencasosaplicadoaldiagnsticomdicoutilizandoclasificadoresmulticlaseunestudiopreliminar-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 = {Razonamiento basado en casos aplicado al diagnóstico médico utilizando clasificadores multi-clase: Un estudio preliminar},\n type = {article},\n year = {2017},\n pages = {232-243},\n volume = {8},\n websites = {https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/141},\n month = {2},\n id = {1160d31c-9bc4-3569-b3e6-51a813010744},\n created = {2021-02-10T05:25:39.004Z},\n file_attached = {false},\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\n last_modified = {2021-02-10T05:25:39.004Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {true},\n hidden = {false},\n citation_key = {Viveros-Melo2017},\n source_type = {article},\n private_publication = {false},\n abstract = {CBR ha demostrado ser apropiado para trabajar con datos de dominios poco estructurados o situaciones donde es difícil la adquisición de conocimiento, como es el caso del diagnóstico médico, donde es posible identificar enfermedades como: cáncer, predicción de epilepsia y diagnóstico de apendicitis. Algunas de las tendencias que se pueden desarrollar para CBR en la ciencia de la salud están orientadas a reducir el número de características en datos de gran dimensión. Una contribución importante puede ser la estimación de probabilidades de pertenencia a cada clase para los nuevos casos. Con el fin de representar adecuadamente la base de datos y evitar los inconvenientes causados por la alta dimensión, ruido y redundancia de los mimos, en este trabajo, se utiliza varios algoritmos en la etapa de pre-procesamiento para realizar una selección de variables y reducción de dimensiones. Además, se realiza una comparación del rendimiento de algunos clasificadores multi-clase representativos para identificar el más eficaz e incluirlo en un esquema CBR. En particular, se emplean cuatro técnicas de clasificación y dos técnicas de reducción para hacer un estudio comparativo de clasificadores multi-clase sobre CBR},\n bibtype = {article},\n author = {Viveros-Melo, D and Ortega-Adarme, M and Blanco Valencia, X and Castro-Ospina, A E and Murillo Rendón, S and Peluffo-Ordóñez, D H},\n doi = {10.29019/enfoqueute.v8n1.141},\n journal = {Enfoque UTE},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  CBR ha demostrado ser apropiado para trabajar con datos de dominios poco estructurados o situaciones donde es difícil la adquisición de conocimiento, como es el caso del diagnóstico médico, donde es posible identificar enfermedades como: cáncer, predicción de epilepsia y diagnóstico de apendicitis. Algunas de las tendencias que se pueden desarrollar para CBR en la ciencia de la salud están orientadas a reducir el número de características en datos de gran dimensión. Una contribución importante puede ser la estimación de probabilidades de pertenencia a cada clase para los nuevos casos. Con el fin de representar adecuadamente la base de datos y evitar los inconvenientes causados por la alta dimensión, ruido y redundancia de los mimos, en este trabajo, se utiliza varios algoritmos en la etapa de pre-procesamiento para realizar una selección de variables y reducción de dimensiones. Además, se realiza una comparación del rendimiento de algunos clasificadores multi-clase representativos para identificar el más eficaz e incluirlo en un esquema CBR. En particular, se emplean cuatro técnicas de clasificación y dos técnicas de reducción para hacer un estudio comparativo de clasificadores multi-clase sobre CBR\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"blancovalencia-becerra-castroospina-ortegaadarme-viverosmelo-peluffoordez-kernelbasedframeworkforspectraldimensionalityreductionandclusteringformulationatheoreticalstudy-2017\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://revistas.usal.es/index.php/2255-2863/article/view/ADCAIJ2017613140\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'blancovalencia-becerra-castroospina-ortegaadarme-viverosmelo-peluffoordez-kernelbasedframeworkforspectraldimensionalityreductionandclusteringformulationatheoreticalstudy-2017', 'http://revistas.usal.es/index.php/2255-2863/article/view/ADCAIJ2017613140', event);\">\n    Kernel-based framework for spectral dimensionality reduction and clustering formulation: A theoretical study.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  BLANCO VALENCIA,  X., P.; BECERRA,  M., A.; CASTRO OSPINA,  A., E.; ORTEGA ADARME,  M.; VIVEROS MELO,  D.;  and PELUFFO ORDÓÑEZ,  D., H.\n</span>\n\n  \n\n</span>\n\n  <i>ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal</i>, 6(1): 31.  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://revistas.usal.es/index.php/2255-2863/article/view/ADCAIJ2017613140\"\n     onclick=\"log_download('blancovalencia-becerra-castroospina-ortegaadarme-viverosmelo-peluffoordez-kernelbasedframeworkforspectraldimensionalityreductionandclusteringformulationatheoreticalstudy-2017', 'http://revistas.usal.es/index.php/2255-2863/article/view/ADCAIJ2017613140', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Kernel-based framework for spectral dimensionality reduction and clustering formulation: A theoretical study [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/10.14201/ADCAIJ2017613140\"\n     onclick=\"log_download('blancovalencia-becerra-castroospina-ortegaadarme-viverosmelo-peluffoordez-kernelbasedframeworkforspectraldimensionalityreductionandclusteringformulationatheoreticalstudy-2017', 'http://doi.org/10.14201/ADCAIJ2017613140', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/blancovalencia-becerra-castroospina-ortegaadarme-viverosmelo-peluffoordez-kernelbasedframeworkforspectraldimensionalityreductionandclusteringformulationatheoreticalstudy-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('blancovalencia-becerra-castroospina-ortegaadarme-viverosmelo-peluffoordez-kernelbasedframeworkforspectraldimensionalityreductionandclusteringformulationatheoreticalstudy-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 = {Kernel-based framework for spectral dimensionality reduction and clustering formulation: A theoretical study},\n type = {article},\n year = {2017},\n pages = {31},\n volume = {6},\n websites = {http://revistas.usal.es/index.php/2255-2863/article/view/ADCAIJ2017613140},\n id = {cc749f68-ecdc-31d3-9aa6-703c96831649},\n created = {2021-02-10T05:25:39.021Z},\n file_attached = {false},\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\n last_modified = {2021-02-10T05:25:39.021Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {true},\n hidden = {false},\n citation_key = {BLANCOVALENCIA2017},\n source_type = {article},\n private_publication = {false},\n abstract = {See, stats, and : https :// www. researchgate. net / publication/ 315475649 Kernel-based dimensionality formulation: A Article DOI : 10 . 14201 / ADCAIJ2017613140 CITATIONS 0 READS 57 6 , including : Some : DATA Case (CBR) for Xiomara Universidad 8 SEE Miguel Institución 35 SEE A . E . Castro - Ospina Instituto 26 SEE Diego Universidad 136 SEE All . The . KEYWORD ABSTRACT Kernel PCA ; Spectral clustering ; Support vector machine . This work outlines a unified formulation to represent spectral approaches for both dimensionality reduction and clustering . Proposed formulation starts with a generic latent variable model in terms of the projected input data matrix . Particularly , such a projection maps data onto a unknown high - dimensional space . Regarding this mod - el , a generalized optimization problem is stated using quadratic formulations and a least - squares support vector machine . The solution of the optimization is addressed through a primal - dual scheme . Once latent variables and parameters are determined , the resultant model outputs a versatile projected matrix able to represent data in a low - dimensional space , as well as to provide information about clusters . Particularly , proposed formulation yields solutions for kernel spectral clustering and weighted - ker - nel principal component analysis .},\n bibtype = {article},\n author = {BLANCO VALENCIA, Xiomara Patricia and BECERRA, M A and CASTRO OSPINA, A E and ORTEGA ADARME, M and VIVEROS MELO, D and PELUFFO ORDÓÑEZ, D H},\n doi = {10.14201/ADCAIJ2017613140},\n journal = {ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  See, stats, and : https :// www. researchgate. net / publication/ 315475649 Kernel-based dimensionality formulation: A Article DOI : 10 . 14201 / ADCAIJ2017613140 CITATIONS 0 READS 57 6 , including : Some : DATA Case (CBR) for Xiomara Universidad 8 SEE Miguel Institución 35 SEE A . E . Castro - Ospina Instituto 26 SEE Diego Universidad 136 SEE All . The . KEYWORD ABSTRACT Kernel PCA ; Spectral clustering ; Support vector machine . This work outlines a unified formulation to represent spectral approaches for both dimensionality reduction and clustering . Proposed formulation starts with a generic latent variable model in terms of the projected input data matrix . Particularly , such a projection maps data onto a unknown high - dimensional space . Regarding this mod - el , a generalized optimization problem is stated using quadratic formulations and a least - squares support vector machine . The solution of the optimization is addressed through a primal - dual scheme . Once latent variables and parameters are determined , the resultant model outputs a versatile projected matrix able to represent data in a low - dimensional space , as well as to provide information about clusters . Particularly , proposed formulation yields solutions for kernel spectral clustering and weighted - ker - nel principal component analysis .\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"viveros-ortega-blanco-peluffo-casebasedreasoningappliedtomedicaldiagnosisusingmulticlassclassifierapreliminarystudy-2017\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/141\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'viveros-ortega-blanco-peluffo-casebasedreasoningappliedtomedicaldiagnosisusingmulticlassclassifierapreliminarystudy-2017', 'https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/141', event);\">\n    Case based reasoning applied to medical diagnosis using multi-class classifier : A preliminary study.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Viveros,  D.; Ortega,  M.; Blanco,  X.;  and Peluffo,  D.\n</span>\n\n  \n\n</span>\n\n  <i>Enfoque UTE</i>.  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=\"https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/141\"\n     onclick=\"log_download('viveros-ortega-blanco-peluffo-casebasedreasoningappliedtomedicaldiagnosisusingmulticlassclassifierapreliminarystudy-2017', 'https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/141', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Case based reasoning applied to medical diagnosis using multi-class classifier : A preliminary study [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/viveros-ortega-blanco-peluffo-casebasedreasoningappliedtomedicaldiagnosisusingmulticlassclassifierapreliminarystudy-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('viveros-ortega-blanco-peluffo-casebasedreasoningappliedtomedicaldiagnosisusingmulticlassclassifierapreliminarystudy-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  \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 = {Case based reasoning applied to medical diagnosis using multi-class classifier : A preliminary study},\n type = {article},\n year = {2017},\n keywords = {Case based reasoning,High dimensionality,Variable selection},\n websites = {https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/141},\n id = {f84b9677-a988-3a31-bbb9-3588d5357dc9},\n created = {2021-02-10T05:25:39.083Z},\n file_attached = {false},\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\n last_modified = {2021-02-10T05:25:39.083Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {true},\n hidden = {false},\n citation_key = {Viveros2017},\n source_type = {article},\n private_publication = {false},\n abstract = {Case-based reasoning (CBR) is a process used for computer processing that tries to mimic the behavior of a human expert in making decisions regarding a subject and learn from the experience of past cases. CBR has demonstrated to be appropriate for working with unstructured domains data or difficult knowledge acquisition situations, such as medical diagnosis, where it is possible to identify diseases such as: cancer diagnosis, epilepsy prediction and appendicitis diagnosis. Some of the trends that may be developed for CBR in the health science are oriented to reduce the number of features in highly dimensional data. An important contribution may be the estimation of probabilities of belonging to each class for new cases. In this paper, in order to adequately represent the database and to avoid the inconveniences caused by the high dimensionality, noise and redundancy, a number of algorithms are used in the preprocessing stage for performing both variable selection and dimension reduction procedures. Also, a comparison of the performance of some representative multi-class classifiers is carried out to identify the most effective one to include within a CBR scheme. Particularly, four classification techniques and two reduction techniques are employed to make a comparative study of multi- class classifiers on CBR.},\n bibtype = {article},\n author = {Viveros, Diana and Ortega, Mabel and Blanco, Xiomara and Peluffo, Diego},\n journal = {Enfoque UTE}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Case-based reasoning (CBR) is a process used for computer processing that tries to mimic the behavior of a human expert in making decisions regarding a subject and learn from the experience of past cases. CBR has demonstrated to be appropriate for working with unstructured domains data or difficult knowledge acquisition situations, such as medical diagnosis, where it is possible to identify diseases such as: cancer diagnosis, epilepsy prediction and appendicitis diagnosis. Some of the trends that may be developed for CBR in the health science are oriented to reduce the number of features in highly dimensional data. An important contribution may be the estimation of probabilities of belonging to each class for new cases. In this paper, in order to adequately represent the database and to avoid the inconveniences caused by the high dimensionality, noise and redundancy, a number of algorithms are used in the preprocessing stage for performing both variable selection and dimension reduction procedures. Also, a comparison of the performance of some representative multi-class classifiers is carried out to identify the most effective one to include within a CBR scheme. Particularly, four classification techniques and two reduction techniques are employed to make a comparative study of multi- class classifiers on CBR.\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=\"peluffoordez-becerra-castroospina-blancovalencia-alvaradoprez-thern-anayaisaza-advancesinintelligentsystemsandcomputing-2016\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/978-3-319-40162-1_28\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'peluffoordez-becerra-castroospina-blancovalencia-alvaradoprez-thern-anayaisaza-advancesinintelligentsystemsandcomputing-2016', 'http://link.springer.com/10.1007/978-3-319-40162-1_28', event);\">\n    On the Relationship Between Dimensionality Reduction and Spectral Clustering from a Kernel Viewpoint.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Peluffo-Ordóñez,  D., H.; Becerra,  M., A.; Castro-Ospina,  A., E.; Blanco-Valencia,  X.; Alvarado-Pérez,  J., C.; Therón,  R.;  and Anaya-Isaza,  A.\n</span>\n\n  \n\n</span>\n\n  Advances in Intelligent Systems and Computing, pages 255-264.  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://link.springer.com/10.1007/978-3-319-40162-1_28\"\n     onclick=\"log_download('peluffoordez-becerra-castroospina-blancovalencia-alvaradoprez-thern-anayaisaza-advancesinintelligentsystemsandcomputing-2016', 'http://link.springer.com/10.1007/978-3-319-40162-1_28', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Advances in Intelligent Systems and Computing [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/10.1007/978-3-319-40162-1_28\"\n     onclick=\"log_download('peluffoordez-becerra-castroospina-blancovalencia-alvaradoprez-thern-anayaisaza-advancesinintelligentsystemsandcomputing-2016', 'http://doi.org/10.1007/978-3-319-40162-1_28', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/peluffoordez-becerra-castroospina-blancovalencia-alvaradoprez-thern-anayaisaza-advancesinintelligentsystemsandcomputing-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  &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('peluffoordez-becerra-castroospina-blancovalencia-alvaradoprez-thern-anayaisaza-advancesinintelligentsystemsandcomputing-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  \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;\">@inbook{\n type = {inbook},\n year = {2016},\n keywords = {Dimensionality reduction,Generalized kernel formulation,Kernel PCA,Spectral clustering,Support vector machine},\n pages = {255-264},\n websites = {http://link.springer.com/10.1007/978-3-319-40162-1_28},\n id = {2f1f2725-75df-38fe-a220-32d52511547c},\n created = {2021-02-10T05:25:38.981Z},\n file_attached = {false},\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\n last_modified = {2021-02-10T05:25:38.981Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {true},\n hidden = {false},\n citation_key = {Peluffo-Ordonez2016},\n source_type = {incollection},\n private_publication = {false},\n abstract = {This paper presents the development of a unified view of spectral clustering and unsupervised dimensionality reduction approaches within a generalized kernel framework. To do so, the authors propose a multipurpose latent variable model in terms of a high-dimensional representation of the input data matrix, which is incorporated into a least-squares support vector machine to yield a generalized optimization problem. After solving it via a primal-dual procedure, the final model results in a versatile projected matrix able to represent data in a low-dimensional space, as well as to provide information about clusters. Specifically, our formulation yields solutions for kernel spectral clustering and weighted-kernel principal component analysis.},\n bibtype = {inbook},\n author = {Peluffo-Ordóñez, D H and Becerra, M A and Castro-Ospina, A E and Blanco-Valencia, X and Alvarado-Pérez, J C and Therón, R and Anaya-Isaza, A},\n doi = {10.1007/978-3-319-40162-1_28},\n chapter = {On the Relationship Between Dimensionality Reduction and Spectral Clustering from a Kernel Viewpoint},\n title = {Advances in Intelligent Systems and Computing}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This paper presents the development of a unified view of spectral clustering and unsupervised dimensionality reduction approaches within a generalized kernel framework. To do so, the authors propose a multipurpose latent variable model in terms of a high-dimensional representation of the input data matrix, which is incorporated into a least-squares support vector machine to yield a generalized optimization problem. After solving it via a primal-dual procedure, the final model results in a versatile projected matrix able to represent data in a low-dimensional space, as well as to provide information about clusters. Specifically, our formulation yields solutions for kernel spectral clustering and weighted-kernel principal component analysis.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2013\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2013')\"\n      onkeypress=\"toggleGroup('group_2013')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2013</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=\"blanco-rodrguez-corchado-zato-casebasedreasoningappliedtomedicaldiagnosisandtreatment-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.springer.com/chapter/10.1007/978-3-319-00551-5_17\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'blanco-rodrguez-corchado-zato-casebasedreasoningappliedtomedicaldiagnosisandtreatment-2013', 'https://link.springer.com/chapter/10.1007/978-3-319-00551-5_17', event);\">\n    Case-Based Reasoning applied to medical diagnosis and treatment.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Blanco,  X.; Rodríguez,  S.; Corchado,  J., M.;  and Zato,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Advances in Intelligent Systems and Computing</i>.  2013.\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://link.springer.com/chapter/10.1007/978-3-319-00551-5_17\"\n     onclick=\"log_download('blanco-rodrguez-corchado-zato-casebasedreasoningappliedtomedicaldiagnosisandtreatment-2013', 'https://link.springer.com/chapter/10.1007/978-3-319-00551-5_17', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Case-Based Reasoning applied to medical diagnosis and treatment [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/10.1007/978-3-319-00551-5_17\"\n     onclick=\"log_download('blanco-rodrguez-corchado-zato-casebasedreasoningappliedtomedicaldiagnosisandtreatment-2013', 'http://doi.org/10.1007/978-3-319-00551-5_17', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/blanco-rodrguez-corchado-zato-casebasedreasoningappliedtomedicaldiagnosisandtreatment-2013\"\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('blanco-rodrguez-corchado-zato-casebasedreasoningappliedtomedicaldiagnosisandtreatment-2013')\" -->\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 = {Case-Based Reasoning applied to medical diagnosis and treatment},\n type = {article},\n year = {2013},\n websites = {https://link.springer.com/chapter/10.1007/978-3-319-00551-5_17},\n id = {600eb85a-b715-3d74-bb0a-cc66a6724ebe},\n created = {2021-02-10T05:25:39.109Z},\n file_attached = {false},\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\n last_modified = {2021-02-10T05:25:39.109Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {true},\n hidden = {false},\n citation_key = {Blanco2013},\n source_type = {article},\n private_publication = {false},\n abstract = {The Case-Based Reasoning (CBR) is an appropriate methodology to apply in diagnosis and treatment. Research in CBR is growing and there are shortcomings, especially in the adaptation mechanism. In this paper, besides presenting a methodological review of the technology applied to the diagnostics and health sector published in recent years, a new proposal is presented to improve the adaptation stage. This proposal is focused on preparing the data to create association rules that help to reduce the number of cases and facilitate learning adaptation rules. ©Springer International Publishing Switzerland 2013.},\n bibtype = {article},\n author = {Blanco, Xiomara and Rodríguez, Sara and Corchado, Juan M and Zato, Carolina},\n doi = {10.1007/978-3-319-00551-5_17},\n journal = {Advances in Intelligent Systems and Computing}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The Case-Based Reasoning (CBR) is an appropriate methodology to apply in diagnosis and treatment. Research in CBR is growing and there are shortcomings, especially in the adaptation mechanism. In this paper, besides presenting a methodological review of the technology applied to the diagnostics and health sector published in recent years, a new proposal is presented to improve the adaptation stage. This proposal is focused on preparing the data to create association rules that help to reduce the number of cases and facilitate learning adaptation rules. ©Springer International Publishing Switzerland 2013.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2006\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2006')\"\n      onkeypress=\"toggleGroup('group_2006')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2006</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=\"blanco-gamboa-lafundacincardiovasculardecolombiaalavanguardiadelatecnologa-2006\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.scielo.org.co/pdf/rcca/v13n2/v13n2a5.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'blanco-gamboa-lafundacincardiovasculardecolombiaalavanguardiadelatecnologa-2006', 'http://www.scielo.org.co/pdf/rcca/v13n2/v13n2a5.pdf', event);\">\n    La Fundación Cardiovascular de Colombia a la vanguardia de la tecnología.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Blanco,  X.;  and Gamboa,  W.\n</span>\n\n  \n\n</span>\n\n  <i>Revista Colombiana de Cardiologia</i>.  2006.\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.scielo.org.co/pdf/rcca/v13n2/v13n2a5.pdf\"\n     onclick=\"log_download('blanco-gamboa-lafundacincardiovasculardecolombiaalavanguardiadelatecnologa-2006', 'http://www.scielo.org.co/pdf/rcca/v13n2/v13n2a5.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"La Fundación Cardiovascular de Colombia a la vanguardia de la tecnología [pdf]\"\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/blanco-gamboa-lafundacincardiovasculardecolombiaalavanguardiadelatecnologa-2006\"\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('blanco-gamboa-lafundacincardiovasculardecolombiaalavanguardiadelatecnologa-2006')\" -->\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</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 = {La Fundación Cardiovascular de Colombia a la vanguardia de la tecnología},\n type = {article},\n year = {2006},\n keywords = {Diseases of the circulatory (Cardiovascular) syste,RC666-701,bioengineering,bioengineering specialities,bioingeniería,especialidades de la bioingeniería,new technologies,nuevas tecnologías},\n websites = {http://www.scielo.org.co/pdf/rcca/v13n2/v13n2a5.pdf},\n id = {3c1bf456-7f82-394d-a42a-2bac5a87348b},\n created = {2021-02-10T05:25:39.048Z},\n file_attached = {false},\n profile_id = {dcbddeb4-43a7-32ca-8726-8f47f33c5362},\n last_modified = {2021-02-10T05:25:39.048Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {true},\n hidden = {false},\n citation_key = {Blanco2006},\n source_type = {article},\n private_publication = {false},\n abstract = {Background: the Colombian Cardiovascular Foundation is aware of the importance of investing in research, development and innovation in order to incorporate and use scientific and technological advances that may contribute to the socio-economical development of the region and the country. Therefore, it has incremented its strategies to promote both a technological culture in our society, and the development of new local technologies or the adaptation of foreign ones to our needs. To achieve these goals, the Colombian Cardiovascular Foundation has created areas such as the strategic business unit FCV. Soft Software Factory, the bioengineering research group, the pediatric research unit and the unit of computer technology, that demand the integration of processes of technological development and the incorporation of new technologies to the regular clinical practice in a third complexity level institution. Objective: to describe the experience of the Colombian Cardiovascular Foundation in the integration of bioengineering and its specialties to the conventional clinical practice. Conclusions: the utilization of bioengineering in the conventional clinical practice favors institutional competitivity and motivates the improvement of the patients&#x27; quality of life, as it allows the creation of new tools to support the medical decisions in an efficient and timely way.},\n bibtype = {article},\n author = {Blanco, Xiomara and Gamboa, Wilson},\n journal = {Revista Colombiana de Cardiologia}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Background: the Colombian Cardiovascular Foundation is aware of the importance of investing in research, development and innovation in order to incorporate and use scientific and technological advances that may contribute to the socio-economical development of the region and the country. Therefore, it has incremented its strategies to promote both a technological culture in our society, and the development of new local technologies or the adaptation of foreign ones to our needs. To achieve these goals, the Colombian Cardiovascular Foundation has created areas such as the strategic business unit FCV. Soft Software Factory, the bioengineering research group, the pediatric research unit and the unit of computer technology, that demand the integration of processes of technological development and the incorporation of new technologies to the regular clinical practice in a third complexity level institution. Objective: to describe the experience of the Colombian Cardiovascular Foundation in the integration of bioengineering and its specialties to the conventional clinical practice. Conclusions: the utilization of bioengineering in the conventional clinical practice favors institutional competitivity and motivates the improvement of the patients' quality of life, as it allows the creation of new tools to support the medical decisions in an efficient and timely way.\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);