Cardiovascular diseases prediction using various machine learning techniques

Abstract

Prediction of cardiovascular diseases is one of the crucial aspects which every healthcare organization has to do with. Prediction of cardiovascular disease well in time may save the life of patients. In this paper, we applied various machine learning techniques for cardiovascular disease or heart disease prediction. In the urge to provide an efficient technique for the prediction of cardiovascular diseases, we have used UCI heart disease data. This data set is dedicated to classification problems related to cardiovascular disease patients. To predict this disease various machine learning techniques like KNN, Logistic Regression, Random Forest, Decision Tree, and naive Bayes have been tested on Data Set. It has been found from the conducted experiments that the results obtained by the Gaussian Naïve Bayes have given superior results compared to other techniques.