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dc.contributor.authorDomínguez Olmedo, Juan Luis 
dc.contributor.authorMata Vázquez, Jacinto 
dc.contributor.authorPachón Álvarez, Victoria 
dc.contributor.authorLópez Guerra, José L.
dc.identifier.citationDomínguez-Olmedo, J. L., Mata, J., Pachón, V., & Lopez-Guerra, J. L. (2018). A Rule-based Method Applied to the Imbalanced Classification of Radiation Toxicity. En Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies. SCITEPRESS - Science and Technology Publications.
dc.description.abstractThis paper describes a rule-based classifier (DEQAR-C), which is set up by the combination of selected rules after a two-phase process. In the first phase, the rules are generated and sorted for each class, and then a selection is performed to obtain a final list of rules. A real imbalanced dataset regarding the toxicity during and after radiation therapy for prostate cancer has been employed in a comparison with other predictive methods (rule-based, artificial neural networks, trees, Bayesian and logistic regression). DEQAR-C produced excellent results in an evaluation regarding several performance measures (accuracy, Matthews correlation coefficient, sensitivity, specificity, precision, recall and F-measure) and by using cross-validation. Therefore, it was employed to obtain a predictive model using the full data. The resultant model is easily interpretable, combining three rules with two variables, and suggesting conditions that are mostly confirmed by the medical literature.es_ES
dc.publisherScience and Technology Publicationses_ES
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.subject.otherImbalanced Data Classificationes_ES
dc.subject.otherRules Discoveryes_ES
dc.subject.otherProstate Canceres_ES
dc.titleA Rule-based Method Applied to the Imbalanced Classification of Radiation Toxicityes_ES

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