Author/Authors :
İŞLER, Yalçın Zonguldak Karaelmas Üniversitesi - Elektrik ve Elektronik Mühendisliği Bölümü, Turkey , NARİN, Ali Zonguldak Karaelmas Üniversitesi - Elektrik ve Elektronik Mühendisliği Bölümü, Turkey
Title Of Article :
Diagnosis of the Patients with Congestive Heart Failure using k-Means Algorithm in WEKA Software
Abstract :
In this study, the accuracy of k-Means clustering algorithm, implemented in WEKA software, in the analysis of heart rate variability (HRV) that are used in discriminating the patients with congestive heart failure (CHF) from normal subjects is investigated. After being obtained from 29 CHF patients and 54 normal subjects, HRV measures were applied to k-Means clustering algorithm using WEKA software. As a result, the maximum discrimination accuracy of 98.79% was achieved when only four clusters were used. Additionally, information about the choices given in WEKA software, which has been widely used in the data mining field and is free of charge, was also presented.
NaturalLanguageKeyword :
WEKA , Congestive Heart Failure , Heart Rate Variability , k , Means
JournalTitle :
Sdu Journal Of Technical Sciences
