• R. Jayapradha
• Dr. S. Ravi
• A. Saranya

In the modern world, one of the most dangerous and crucial disease is the heart disease which leads the causes of more number of deaths. In order to diagnose, the great prerequisite for the detection of heart disease is heart sound. Now a days, extensive research has been carried out for different feature selection and classification technique. According to this survey paper we deal with the most important feature for the detection of heart disease that is feature evaluation or ranking and feature selection. They are the most important features to the classification problem. During classification section we compared many neural network techniques which give 90% and above accuracy as classifier for heart valve disease detection. Then, a comparative study is applied to determine the most effective techniques that are capable for the detection of heart valve disease with a high accuracy.

Neural networks, Heart sound, Deep learning.

"Classification of Heart Sounds using Neural Networks – A Survey", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.312-320, April-2019, Available :http://www.jetir.org/papers/JETIR1904H56.pdf

"Classification of Heart Sounds using Neural Networks – A Survey", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp312-320, April-2019, Available at : http://www.jetir.org/papers/JETIR1904H56.pdf