Cardiovascular disease prediction using machine learning tools

Abstract

Cardiovascular disease deals with the disarray of blood vessels and heart. It is one of the leading causes of death globally. A doctor cannot be equally skilled in each and every domain and their availability is limited in most parts, especially in a country like India. Since the inception of machine learning, healthcare has been one of the most rewarding fields for its application. In this paper, we compared the accuracy of different machine learning algorithms like multilayer perceptron, k-nearest neighbour, logistic regression and support vector machine in approximating the severity level of cardiovascular disease in a person considering various physiological parameters. The heart disease dataset is taken from the UCI machine learning repository which is publicly available and is the most widely used dataset for heart disease prediction.