CLASSIFICATION OF HEART SOUNDS BASED ON THE LEAST SQUARES SUPPORT VECTOR MACHINE

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dc.contributor.authorGuraksin, Gur Emre
dc.contributor.authorUguz, Harun
dc.date.accessioned2020-03-26T18:13:55Z
dc.date.available2020-03-26T18:13:55Z
dc.date.issued2011
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractThe heart is of crucial significance to human beings. Auscultation with a stethoscope is regarded as one of the pioneer methods used in the diagnosis of heart diseases. However, the fact that auscultation via a stethoscope depends on the skills of the physician's auscultation or his/her experience may lead to some problems in diagnosis. Therefore, the use of an artificial intelligence method in the diagnosis of heart sounds may help the physicians in a clinical environment. In this study, primarily, heart sound signals in numerical format were separated into sub-bands through discrete wavelet transform. Next, the entropy of each sub-band was calculated by using the Shannon entropy algorithm to reduce the dimensionality of the feature vectors with the help of the discrete wavelet transform. The reduced features of three types of heart sound signals were used as input patterns of the least square support vector machines and they were classified by least square support vector machines. In the method used, 96.6% of the classification performance was obtained. The classification performance of the method used was compared with the classification performance of previous studies which were applied to the same data set, and the superiority of the system used was demonstrated.en_US
dc.description.sponsorshipScientific Research Project of Selcuk UniversitySelcuk Universityen_US
dc.description.sponsorshipThe authors wish to acknowledge the Afyon Kocatepe University Scientific Research Council with the Project number "07.AFMY0.01" for the collection of the heart sounds used in this study. This study has been supported by Scientific Research Project of Selcuk Universityen_US
dc.identifier.endpage7144en_US
dc.identifier.issn1349-4198en_US
dc.identifier.issn1349-418Xen_US
dc.identifier.issue12en_US
dc.identifier.startpage7131en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/26229
dc.identifier.volume7en_US
dc.identifier.wosWOS:000297957500037en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherICIC INTERNATIONALen_US
dc.relation.ispartofINTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROLen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectLeast squares support vector machineen_US
dc.subjectDiscrete wavelet transformen_US
dc.subjectShannon entropyen_US
dc.subjectHeart soundsen_US
dc.titleCLASSIFICATION OF HEART SOUNDS BASED ON THE LEAST SQUARES SUPPORT VECTOR MACHINEen_US
dc.typeArticleen_US

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