Heart Disease Prediction System Using Artificial Neural Network, Radial Basis Function and Case Based Reasoning

摘要

Heart disease is one of the most hazardous diseases to human which shows the way to death all over the world since 15 years. Many researches have been done with the techniques of knowledge discovery in various fields for Heart Disease prediction and have shown the acceptable levelsof accuracy. By investigating the survey of those accuracy levels, this research paper is proposed to help doctors not only to diagnose and predict the heart disease by achieving accuracy levels but also helps to prescribe the medicine successfully according to the predicted disease. In thepaper assessment is done by two methodologies ANN (Artificial neural network) by testing the datasets, CBR (Case Based Reasoning) image similarity search by mapping the similarities of images of old patients stored in database for prediction of heart disease. The result of the evaluation ofCBR is also implemented for prescribing medicine from the history of old patients with Generalized Regression Neural Network and Radial basis function successfully.