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A Study of Classification of Heart Murmurs using Shannon Entropy and Neural Network  

Eum, Sang-Hee (동주대학교)
Publication Information
Journal of the Institute of Convergence Signal Processing / v.16, no.4, 2015 , pp. 134-138 More about this Journal
Abstract
Heart sound is used for a basic clinical examination to check for abnormalities in the lungs and heart that can be heard with a stethoscope or phonocardiography. In this paper, we try to find an easier and non-invasive method to diagnose heart diseases using neural network classifier. The classifier has been developed for one normal heart sound and five murmurs by using Shannon entropy and conjugate scaled back propagation algorithm. The experimental results showed that the classification is possible with 1.63185e-6 of classification error.
Keywords
Heart Murmurs; Classification; Shannon Entropy; Neural Network;
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