A Survey and Analysis on Predicting Heart Disease Using Machine Learning Techniques

Abstract

The early prognosis of cardiovascular diseases can
aid in making decisions to lifestyle changes in high-risk patients and in turn reduce their complications. Predicting heart disease using machine learning techniques has been a popular and promising area of research in recent years. Machine learning models can analyze large amounts of medical data and extract patterns and relationships that can help in predicting the likelihood of heart disease in individuals. We can conduct a survey and analysis to predict heart disease using machine learning techniques. Predicting heart disease using machine learning techniques is a promising area of research, and there have been several studies conducted in this field. Here is an overview of a survey and analysis of some of the most prominent studies on this topic. This paper compares the accuracies of different machine learning algorithms on the Cleveland Heart Disease Database in order to present an accurate model of predicting heart disease.