A Novel Approach for Prediction of Cardio Vascular Disease: An Improved Genetic Algorithm Approach Using Classifiers

Abstract

Data mining is an important part in Heart Disease (HD). In medical domain gather information from past experiments and determine them to find trends and results to present situations. For the exact prediction, heterogeneous ensemble classifier is proposed for the early stage diagnosis.  It identifies causes, symptoms and estimates the treatment for the Dilated Cardiomyopathy, which is due to the heart muscle inflection.  The proposed system will be significant with prognosis analysis for the exact prediction and diagnosis of the dilated cardiomyopathy and heart failure. Improved Genetic algorithm (IGA) model generates greater accuracy level for all HD compared to other classifiers.