Bayesian Belief Network for Heart Disease Prediction

Abstract

With millions of people dying of Cardiovascular diseases (CVDs) annually, the application of Artificial Intelligence in the prediction and diagnosis of these diseases has become essential. Researchers have used various Machine Learning techniques to predict heart diseases in patients. Bayesian Belief Networks (BBN) are often used as a popular technique for disease prediction and diagnosis because of their interpretability and flexibility. However, not much work has been done on heart disease prediction using BBN. In this paper, we use Bayesian Belief Networks to predict the likelihood of cardiovascular diseases in patients. The proposed model takes patient information on different risk factors associated with cardiovascular diseases and builds a Bayesian Belief Network that predicts the likelihood of heart diseases in people.