Methodical Prediction of Cardiovascular Disease Using Consolidated Machine Learning Classification Algorithms and Analysis - Datta, Aparna; Ghosh, Sreeja (International Journal of Computer Sciences and Engineering, 2026)
Heart disease has been a serious threat to mankind. According to research 7 out of 10 people die due to heart failure. In this paper, we have proposed a framework using which we can determine if a person has heart ailments or not. We have used various ML classification algorithms such as Logistic Regression, SVM, Random Forest, Decision tree, KNN, MLP, and Neural Network to determine the existence of heart disease. The best result has been obtained by Random Forest. Timely detection of a disease can save many people’s lives, thereby controlling the mortality rate to some extent.