| dc.contributor.author | Çimen, Emre | |
| dc.contributor.author | Öztürk, Gürkan | |
| dc.contributor.editor | Arabnia, HR | |
| dc.contributor.editor | Deligiannidis, L | |
| dc.contributor.editor | Yang, M | |
| dc.date.accessioned | 2019-10-21T20:41:32Z | |
| dc.date.available | 2019-10-21T20:41:32Z | |
| dc.date.issued | 2016 | |
| dc.identifier.isbn | 978-1-5090-5510-4 | |
| dc.identifier.uri | https://dx.doi.org/10.1109/CSCI.2016.154 | |
| dc.identifier.uri | https://hdl.handle.net/11421/20816 | |
| dc.description | International Conference on Computational Science and Computational Intelligence (CSIC) -- DEC 15-17, 2016 -- Las Vegas, NV | en_US |
| dc.description | WOS: 000405582400147 | en_US |
| dc.description.abstract | Heart disease is one of the important cause of death. In this study, we used ECG data obtained from MIT-BIH database to classify arrhythmias. We select 5 classes; normal beat (N), right bundle branch block (RBBB), left bundle branch block (LBBB), atrial premature contraction (APC) and ventricular premature contraction (VPC). We applied k-means based Polyhedral Conic Functions (k-means PCF) algorithm to classify instances. The performance of the proposed classifier is shown with numerical experiments. With proposed algorithm we obtained 98 % accuracy rate. This test result is compared with other well known classification methods. | en_US |
| dc.description.sponsorship | Amer Council Sci & Educ | en_US |
| dc.description.sponsorship | Anadolu University Scientific Research Projects Commission [1103F035] | en_US |
| dc.description.sponsorship | The authors would like to thank anonymous referees for their criticism and comments which allowed to improve the quality of the paper. The authors also thank to cardiologist Dr. Ozcan Yucel for his help in analyzing the ECG signals, and Prof. Dr. Omer Nezih Gerek for his guiding in signal processing. This study was supported by Anadolu University Scientific Research Projects Commission under the grant no: 1103F035. | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | IEEE | en_US |
| dc.relation.isversionof | 10.1109/CSCI.2016.154 | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Arrhythmia | en_US |
| dc.subject | Classification | en_US |
| dc.subject | Clustering | en_US |
| dc.subject | Mathematical Programming | en_US |
| dc.title | Arrhythmia Classification via k-Means based Polyhedral Conic Functions Algorithm | en_US |
| dc.type | conferenceObject | en_US |
| dc.relation.journal | 2016 International Conference On Computational Science & Computational Intelligence (Csci) | en_US |
| dc.contributor.department | Anadolu Üniversitesi, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü | en_US |
| dc.identifier.startpage | 798 | en_US |
| dc.identifier.endpage | 802 | en_US |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US] |
