Prediction of Heart Disease Using Machine Learning Techniques

Abstract

Heart disease is one of the significant causes of mortality in the world today. Predicting cardio vascular disease has become the critical challenge in the area of clinical data analysis. Machine learning (ML) is very effective in making decisions and predictions from the large quantity of data produced by the health care industry. Machine Learning techniques are used in recent developments in different areas of the Internet of Things (IoT). Various studies provides only a glimpse in predicting heart disease using Machine Learning techniques which aims to get the features by applying ML techniques that results higher accuracy in the prediction of heart disease. The heart disease prediction model is developed using various combinations of classification and feature techniques, which provides performance accuracy of 88.7% using hybrid random forest with linear model (HRFLM).