Design of a Predictive Model for Congenital Heart Disease Using Neural Networks

The proportion of deaths caused by heart disease is the highest in south India (25 per cent) and lowest - 12 per cent - in the central region of India. The prediction of heart disease survivability has been a challenging research problem for many researchers. Since the early dates of the related research, much advancement has been recorded in several related fields. Therefore, the main objective of this manuscript is to report on a research work where we took advantage of those available technological advancements to develop prediction models for heart disease survivability. We used three popular data mining algorithms CART (Classification and Regression Tree), ID3 (Iterative Dichotomized 3) and decision table (DT) extracted from a decision tree or rule-based classifier to develop the prediction models using a large dataset.