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The discrimination of ECG signals using the Data Mining Decision Tree techniques is of crucial importance in the cardiac disease therapy and control of cardiac arrhythmias. Different ECG signals from MIT\/BIH Arrhythmia data base are used for ECG features extraction and analysis. Two pathologies are considered: atrial fibrillation and right bundle branch block. Some decision tree classification algorithms currently in use, including C4.5, Improved C4.5, CHAID (Chi square Automatic Interaction Detector) and Improved CHAID are performed for performance analysis. Promising results have been achieved using the C4.5 classifier, with an overall accuracy of 96.87%.<\/p>","DOI":"10.4018\/jehmc.2012100106","type":"journal-article","created":{"date-parts":[[2012,12,17]],"date-time":"2012-12-17T13:42:27Z","timestamp":1355751747000},"page":"102-120","source":"Crossref","is-referenced-by-count":12,"title":["Comparative Study of ECG Classification Performance Using Decision Tree Algorithms"],"prefix":"10.4018","volume":"3","author":[{"given":"Faiza","family":"Charfi","sequence":"first","affiliation":[{"name":"Electronic and Information Technologies Laboratory, Sfax University, Sfax, Tunisia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali","family":"Kraiem","sequence":"additional","affiliation":[{"name":"Electronic and Information Technologies Laboratory, Sfax University, Sfax, Tunisia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"jehmc.2012100106-0","doi-asserted-by":"publisher","DOI":"10.1109\/51.376752"},{"key":"jehmc.2012100106-1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2006.03.001"},{"key":"jehmc.2012100106-2","doi-asserted-by":"crossref","unstructured":"Cao, R., & Xu, L. 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