Abstract

Abstract:Heart Attacks are the major cause of death in the worldtoday, particularly in India. The need to predict this is a major necessity forimproving the country’s health-care sector. Accurate and precise prediction ofthe heart disease mainly depends on Electrocardiogram (ECG) data and clinicaldata. This information is being fed to a nonlinear disease prediction model.This nonlinear heart function monitoring module is being able to detect heartabnormalities. The proposed system develops an efficient method to acquire theclinical and Electrocardiogram (ECG) data, so as to train the Artificial NeuralNetwork to accurately predict the heart abnormalities if any. The proposedsystem will analyze Electrocardiogram (ECG) and clinical data to train theneural network for predicting chances of the heart attack and then which willgenerate a report predicting the abnormalities in the heart or its functioning.

Keywords: Artificialneural network, Electrocardiogram Data, Clinical Data, heart abnormalities