Effective Heart Disease Prediction Using Machine Learning—Modified KNN

People suffering from heart diseases have been increased these days. Although many instruments are available to predict heart diseases, they are expensive and unaffordable by common people. In this situation, machine learning plays an important role. The main goal of this paper is to predict whether the patient is suffering from heart disease, by using machine learning. Here, five algorithms such as, K-nearest neighbor (KNN), support vector machine (SVM), decision tree (DT), random forest classifier, and modified KNN are used. Based on the accuracy attained by these algorithms, modified KNN that shows 94.0% accuracy which is higher among all the algorithms, and has been considered for the main application, which refers to web application where inputs are taken from the user to predict the presence of heart illness.