Machine Learning based Cardiac Disease Prediction- A Comparative Analysis

Among the living creatures cardiovascular diseases (CVDs), heart-related ailments, are the leading cause of death globally for a number of years and are now acknowledged as the most serious disease in both India and the rest of the world. As a result, early detection of these illnesses is crucial for successful treatment, necessitating the development of a reliable, accurate, and practical approach. Researchers have recently made extensive use of artificial intelligence techniques to aid the medical community and professionals in the identification of heart-related disorders. In order to analyze a huge medical data machine learning methods play a prime role. In this study, a detail comparative analysis of machine learning methods are carried out to predict the cardiac diseases by using real time datasets. The most vibrant methods of logistic regression, random forest, naive Bayes are used to predict the cardiac diseases in which random forest method produces better results in comparison with other methods.