Towards the classification of heart sounds based on convolutional deep neural network

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dc.authorid0000-0003-1614-2639en_US
dc.authorid0000-0002-8721-1219en_US
dc.authorid0000-0003-3210-3664en_US
dc.authorid0000-0003-1840-9958
dc.contributor.authorDemir, Fatih
dc.contributor.authorŞengür, Abdulkadir
dc.contributor.authorBajaj, Varun
dc.contributor.authorPolat, Kemal
dc.date.accessioned2021-06-23T19:51:10Z
dc.date.available2021-06-23T19:51:10Z
dc.date.issued2019
dc.departmentBAİBÜ, Mühendislik Fakültesi, Elektrik Elektronik Mühendisliği Bölümüen_US
dc.description.abstractBackground and objective Heart sound contains various important quantities that help early detection of heart diseases. Many methods have been proposed so far where various signal-processing techniques have been used on heart sounds for heart disease detection. Methods In this paper, a methodology is introduced for heart disease detection based on heart sounds. The proposed method employs three successive stages, such as spectrogram generation, deep feature extraction, and classification. In the spectrogram generation stage, the heart sounds are converted to spectrogram images by using time-frequency transformation. Results The deep features are extracted from three different pre-trained convolutional neural network models such as AlexNet, VGG16, and VGG19. Support vector machine classifier is used in the third stage of the proposed method. The proposed method is evaluated on two datasets, which are taken from The Classifying Heart Sounds Challenge. Conclusions The obtained results are compared with some of the existing methods. The comparisons show that the proposed method outperformed.en_US
dc.identifier.doi10.1007/s13755-019-0078-0
dc.identifier.issn2047-2501
dc.identifier.issue1en_US
dc.identifier.pmid31428314en_US
dc.identifier.scopus2-s2.0-85087281053en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1007/s13755-019-0078-0
dc.identifier.urihttps://hdl.handle.net/20.500.12491/9935
dc.identifier.volume7en_US
dc.identifier.wosWOS:000479150900002en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.institutionauthorPolat, Kemal
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofHealth Information Science And Systemsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectHeart Sounden_US
dc.subjectConvolutional Neural Network (CNN)en_US
dc.subjectModelingen_US
dc.subjectClassificationen_US
dc.titleTowards the classification of heart sounds based on convolutional deep neural networken_US
dc.typeArticleen_US

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