HEART DISEASE PREDICTION USING STACKED GENERALIZATION ENSEMBLE TECHNIQUE

Abstract

The Myocardium, also known as the Heart, is responsible for pumping oxygenated blood to and deoxygenated blood from other human body parts. All the other organs in the human body are dependent on the coherent working of this organ. Cardiovascular diseases are some of the deadliest diseases, which have caused millions of deaths world wide. Early detection of heart diseases is an ongoing and crucial problem in medical science, and various researchers are attempting to improve physician’s ability by devel oping an intelligent medical decision support system. Through this research work, we submit a systematic ensemble-based approach for heart disease prediction. It uses a hy brid combination of Support Vector Machine (SVM) algorithm, Artificial Neural Network (ANN), and Extreme Gradient Boost (XGB) algorithms, which are then combined using the Stacking ensemble method. This system has provided an accuracy of 92% for the prediction of heart disease.