A SYSTEMATIC REVIEW OF PREDICTION OF HEART DISEASES USING SUPERVISED MACHINE LEARNING ALGORITHMS

Abstract

Machine learning algorithms are playing a major role in prediction of heart diseases. As compared to other diseases, heart disease is getting more attention today since it affects humans unexpectedly. Early detection of heart diseases will save human lives. Many researchers have published numerous articles in prediction analysis of heart disease with the support of machine learning algorithms. Especially, supervised learning algorithms are getting more attention with respect to heart diseases prediction. This paper provides a system review of heart diseases prediction with the help of supervised learning algorithms. The impact that heart diseases have on human lives is examined in this paper. It also discusses the various supervised learning algorithms. Tools and datasets used for heart disease prediction are also presented. Performance metrics that are used for heart disease prediction are discussed and examined. We have examined the comparison of various supervised machine learning algorithms with respect to heart diseases prediction. The review clearly identifies the most applied supervised machine learning algorithm by a significant number of research studies.