Prediction of Heart Disease Based on Risk Factors Using

Nowadays, Heart Disease is a major cause of dejection and fatality. All over the world, deaths due to Heart Disease is increasing rapidly than from any other disease. It is very difficult to predict the probable complications regarding Heart Disease well in advance. To identify the probable complications, many systems are made that uses clinical data sets for identifications. Some of the systems predict heart disease based on risk factors. A lot of visible risk factors that are common in Heart Disease patients can be used effectively for diagnosis. System based on risk factors helps not only medical experts for prediction but also warn the patients in advance about the probable presence of heart disease. These systems are also helpful to save money and time. Hence, taking an assumption forward a hybrid technique is proposed for prediction of Heart Disease on basis of risk factors. Data mining tools used for this system is: - Support Vector Machine (SVM) Classifier and Genetic Algorithm. The hybrid implemented technique uses the global optimization advantage of GA for initialization of Support Vector Machines (SVM) Weights. This technique makes system fast, more stable and accurate as compare to others. The system was implemented in MATLAB and on the basis of risk factors an accuracy of implemented system is 95%.