A Review On Machine Learning Approaches For Heart Disease Classificaiton Using Pcg Data

Abstract

Heart Disease Or Cardiovascular Disease (CVD) Is The Leading Cause Of Death In The World. Around 17.9 Million People Die Prematurely Because Of Heart Disorders. Much Of The Deaths Occur In Low And Middle-income Countries [1]. CVD Relates To A Collection Of Heart Or Blood Vessel Malfunction Such As Coronary Heart Disease, Congenital Heart Disease, And Peripheral Arterial Disease. Diagnosis Of These Cardiac Problems Often Involves Listening To The Heart Sounds Through The Phenomenon Of Cardiac Auscultation [2]. One Of The Common Methods To Perform Cardiac Auscultation Electronically Is Through Phonocardiograph. This Paper Presents A Comprehensive Review On Automated Classification Of PCG Data Using Machine Learing. The Contemporary Techniques Along With The Salinet Features Of The Apprapches Used.

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