ANN Model to Predict Coronary Heart Disease Based on Risk Factors

This paper presents a neural network based on Levenberg-Marquardt back-propagation algorithm for prediction of degree of angiographic coronary heart disease. The novelty of this work is training a one hidden layer neural network with Levenberg-Marquardt back-propagation algorithm for multivariate large dataset. An ANN model is developed for prediction of degree of angiographic coronary heart disease, and subsequently, its performance is evaluated using heart disease database obtained from Cleveland Clinic Foundation Database with all attributes are numeric-valued. About 88 cases of different aged angiographic coronary heart disease subjects with 13 attributes have been tested in this model. This study exhibits ANN based prognosis of coronary heart disease and improves the diagnosis accuracy to 95.5 % which is comparably higher with earlier works.