Arrhythmia Disease Prediction System (ADPS) Using Machine Learning Concepts

Abstract

Lifestyle changes refer to modifying things so automatically the food habits is also changed Due to this reason many people are affected by some dreadful diseases like blood pressure cholesterol and some heart related diseases Among these the most dangerous disease is heart diseases this is the main reason for increasing death rate So there is a need to predict the heart disease in the earlier manner the earlier prediction of the heart diseases is easy to cure In medical domain the usage of machine learning concepts is growing every day In this proposed system Machine Learning Algorithms are applied to forecast the Arrhythmia disease in earlier manner Arrhythmia is one of the heart disease which means that the heart beats to quickly or too slowly or sometimes with an abnormal pattern Here to detect the disease by using KNN algorithm Nave Bayes and decision tree Finally the performance of these machine learning algorithms are analyzed in terms of accuracy level Among these algorithms Decision tree algorithm provides 84 accuracy