Prediction of Heart Disease using Machine Learning for Preventive Healthcare

Abstract

Diagnosis of cardiovascular disease starts with a medical history to determine that illness has taken place previously. Risk factors must be measured and then the existence of cardiac disease can be verified by tests. Changes in the operation of the heart can be indicative of cardiac disease. There are several approaches for diagnosing potential cardiovascular disorders. In this paper, a method to detect heart disease using machine learning techniques has been presented which can provide an effective measure of preventive healthcare for heart diseases. The model uses three popular machine learning classification techniques viz. Naïve Bias,SVM and Random Forest have been compared with accuracy results of 86%,82% and 95% respectively.

Keywords: Heart Disease, Classification, Machine learning, Dataset