Comparision of classifier performances in diagnosing congestive heart failure using heart rate variability
In this study, the performance of different discrimination algorithms in the analysis of heart rate variability that are used in discriminating the patients with congestive heart failure from normal subjects were investigated. Classifier algorithms of linear discriminant analysis, k-nearest neighbors, multilayer perceptron, radial basis functions and support vector machines were examined with different parameter values. As a result, the maximum classification accuracy of 91.56% was achieved by using multilayer perceptron with 11 neurons in hidden layer.
| Yazar |
Narin, Ali Özer, Mahmut İşler, Yalçın |
| Yayın Türü | Proceedings |
| Tek Biçim Adres | https://hdl.handle.net/20.500.12628/2262 |
| Tek Biçim Adres | 10.1109/SIU.2013.6531311 |
| Konu Başlıkları |
heart rate variability
heart failure pattern recognition |
| Koleksiyonlar |
Fakülteler Mühendislik Fakültesi Elektrik - Elektronik Mühendisliği Bölümü Bildiri Koleksiyonu (Elektrik - Elektronik Mühendisliği Bölümü) Araştırma Çıktıları | WoS | Scopus | TR-Dizin | PubMed | SOBİAD Scopus İndeksli Yayınlar Koleksiyonu Araştırma Çıktıları | WoS | Scopus | TR-Dizin | PubMed | SOBİAD WoS İndeksli Yayınlar Koleksiyonu |
| Dergi Adı | 2013 21ST SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) |
| Sayfalar | - |
| Yayın Yılı | 2013 |
| Eser Adı [dc.title] | Comparision of classifier performances in diagnosing congestive heart failure using heart rate variability |
| Yazar [dc.contributor.author] | Narin, Ali |
| Yazar [dc.contributor.author] | Özer, Mahmut |
| Yazar [dc.contributor.author] | İşler, Yalçın |
| Yayın Yılı [dc.date.issued] | 2013 |
| Yayıncı [dc.publisher] | IEEE |
| Yayın Türü [dc.type] | proceedings |
| Açıklama [dc.description] | 21st Signal Processing and Communications Applications Conference (SIU) -- APR 24-26, 2013 -- CYPRUS |
| Açıklama [dc.description] | WOS: 000325005300152 |
| Özet [dc.description.abstract] | In this study, the performance of different discrimination algorithms in the analysis of heart rate variability that are used in discriminating the patients with congestive heart failure from normal subjects were investigated. Classifier algorithms of linear discriminant analysis, k-nearest neighbors, multilayer perceptron, radial basis functions and support vector machines were examined with different parameter values. As a result, the maximum classification accuracy of 91.56% was achieved by using multilayer perceptron with 11 neurons in hidden layer. |
| Kayıt Giriş Tarihi [dc.date.accessioned] | 2019-12-23 |
| Açık Erişim Tarihi [dc.date.available] | 2019-12-23 |
| Yayın Dili [dc.language.iso] | tur |
| Konu Başlıkları [dc.subject] | heart rate variability |
| Konu Başlıkları [dc.subject] | heart failure |
| Konu Başlıkları [dc.subject] | pattern recognition |
| Künye [dc.identifier.citation] | Narin, A., Özer, M. ve İşler, Y. (2013). Comparision of classifier performances in diagnosing congestive heart failure using heart rate variability. 2013 21st Signal Processing and Communications Applications Conference (SIU) içinde (ss. 1–4). doi:10.1109/SIU.2013.6531311 |
| Haklar [dc.rights] | info:eu-repo/semantics/closedAccess |
| ISSN [dc.identifier.issn] | 2165-0608 |
| Dergi Adı [dc.relation.journal] | 2013 21ST SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) |
| Tek Biçim Adres [dc.identifier.uri] | https://hdl.handle.net/20.500.12628/2262 |
| Tek Biçim Adres [dc.identifier.uri] | https://doi.org/10.1109/SIU.2013.6531311 |
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