APPLICATION OF MACHINE LEARNING TECHNIQUES IN CLASSIFYING NORMAL AND ABNORMAL ECG HEARTBEATS

Abstract

The vital role played by the heart for the sustenance of humanity is such that the heart be given proper attention and care besides the ribs. The alarming rate of heart defects and increasing death toll calls for the urgent need to improve the ECG platform with enhance machine learning technique the more accurate predictive diagnosis of heart conditions like arrhythmia, stroke and other cardio-vascular disorders. This paper proposed a machine learning approach using ANN and objective methodology to analyse and predict heartbeat condition using heart dataset of 303 patients from kaggle dataset repository and the accuracy level was 88.52 with a validation loss of 34.31 respectively which indicates that with further work with more advance machine learning algorithm the predictive capacity of the model could be optimized