Enhanced Model for Prediction and Classification of Cardiovascular Disease using Decision Tree with Particle Swarm Optimization

Abstract

Data mining is a set of algorithms that can be implemented by tools. It effectively addresses many real-time problems. This data mining focuses on various sectors and related problem. Healthcare is one of the important sector which require more advanced methodologies to predict the disease in an early stage in a more accurate manner. Data mining methods are effective in disease prediction. For making enhanced predictions and classification in Cardio Vascular Disease, the data mining model is proposed with the J48 algorithm with Particle Swarm Optimization (PSO). A Benchmark dataset is used for this research work that contains 14 attributes with two different classes. The experimental results highlight the performance efficiency in the Cardio Vascular Disease prediction and classification.