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Myocardial ınfarction classification with support vector machine models

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dc.contributor.author Güldoğan, Emek
dc.contributor.author Yağmur, Jülide
dc.contributor.author Yoloğlu, Saim
dc.contributor.author Asyalı, Musa Hakan
dc.contributor.author Çolak, Cemil
dc.date.accessioned 2017-12-22T07:17:54Z
dc.date.available 2017-12-22T07:17:54Z
dc.date.issued 2015
dc.identifier.citation Güldoğan, E., Yağmur, J., Yoloğlu, S., Asyalı, M. H., & Çolak, C. (2015). Myocardial Infarction Classification With Support Vector Machine Models. J Turgut Ozal Med Cent, 22(4), 221–224. tr_TR
dc.identifier.uri http://hdl.handle.net/11616/7920
dc.description J Turgut Ozal Med Cent, 22(4), 221–224. tr_TR
dc.description.abstract Aim: Support vector machines (SVM) is one of the classification methods that aims to find the best hyper-plane separating a space into two parts with known positive and negative samples. The goal of this study is to classify myocardial infarction (MI) using SVM models. Material and Methods: The data used in the MI classification contains information related to 184 individuals which is randomly taken from the database created for the Department of Cardiology, Faculty of Medicine, Inonu University. Estimated SVMs are models generated from the SVM-linear and SVM-Radial Based kernel functions. Results: In this study, 90 individuals of the study group (48.9%) are MI patients, while 94 (51.1%) patients are not. The classification success rate is 83.70% for SVM-linear model and 90.76% for the SVM-Radial Based model. Conclusion: In this study, it is observed that SVM-Radial based model presented a better classification performance than the linear SVM model. The use of SVM models based on various kernel type functions can improve disease classification performance. tr_TR
dc.language.iso eng tr_TR
dc.publisher J Turgut Ozal Med Cent tr_TR
dc.relation.isversionof 10.7247/jtomc.2015.2671 tr_TR
dc.rights info:eu-repo/semantics/openAccess tr_TR
dc.subject Support Vector Machines tr_TR
dc.subject Myocardial Infarction tr_TR
dc.subject Classification tr_TR
dc.title Myocardial ınfarction classification with support vector machine models tr_TR
dc.type article tr_TR
dc.relation.journal J Turgut Ozal Med Cent tr_TR
dc.contributor.department İnönü Üniversitesi tr_TR
dc.contributor.authorID 105641 tr_TR
dc.contributor.authorID 103692 tr_TR
dc.contributor.authorID 39164 tr_TR
dc.contributor.authorID 9712 tr_TR
dc.identifier.volume 22 tr_TR
dc.identifier.issue 4 tr_TR
dc.identifier.startpage 221 tr_TR
dc.identifier.endpage 224 tr_TR

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