A Study on Machine Learning Techniques Used for Heart Disease Prediction: A Critical Analysis

Abstract

Among various diseases one of the hazardous diseases that takes uncountable lives every year is heart disease. In todays world, it is believed that one person dies from heart disease every minute. By WHO report number of deaths that take place due to heart disease is 1.75 million, with the number expected to rise to 75 million by 2030. As a result, an accurate and fast heart disease prognosis is a critical necessity for lowering heart disease-related death rates. The Angiography is the easiest and effective clinical test but it has drawback of expensive in cost and many side effects. So, in order to deal with this difficult issue, a significant role in various disease prognosis is shown by ICT. Machine learning is an emerging technology that performs automation from previous available data and shows promising results, it is a subset of artificial intelligence. In this work different literatures related to heart disease and machine learning techniques used in those literatures are critically analyzed and a review of them is summarized in a systematic manner.