CARDIOVASCULAR DISEASE PREDICTION USING RANDOM FOREST

Abstract

Heart plays a vital role in living organisms. Heart disease, which is also known as coronary artery disease, is a leading cause of death globally, exacerbated by various external factors. Nowadays everything has become so simple with the upcoming technologies like machine learning. Machine learning provides a promising solution to this crisis. Machine learning, a subset of artificial intelligence, involves algorithms that help in predicting outcomes and making decisions based on large amounts of data. It has become a buzzword in almost every sector or industry due to its transformative potential. In this study, we employ the Random Forest algorithm to predict heart disease. This model achieved an accuracy of 90.16%, highlighting its potential in accurately predicting heart health status. Although there are many machine learning models available for heart disease prediction, we chose Random Forest for its robustness and reliability.