Improvement of data classification Pertaining to heart diseases using Hybrid optimization technique

Abstract

The medical field is growing at a rapid pace with new diseases are cropping up daily with need for invention of appropriate course of treatment The heart is a muscular organ which is the size of clenched human fist and is responsible for blood circulation Though heartcardiac disease is the name given to diseases affecting the heart in general there are many diseases which come under this name including Coronary Artery Diseases CAD cardiomyopathy Cardio Vascular Disease CVD and so on depending upon the circulation of blood throughout the body. To support clinicians in the diagnosis of heart disease the heart disease data prediction has been so designed to analyze medical data with clinical expertise Through improvement in these predicting systems there can be an enhancement in the quality of medical diagnostic decisions for heart disease newlineData mining plays a crucial part in the prediction of cardiac disease. In newlinethis work the Naïve Bayes NB classifier C45 classifier and Artificial Neural Network ANNBack Propagation BP methods are used These traditional methods are utilized for predicting heart disease newline