Hybridization of Data Mining Techniques for Prediction of Heart Disease

Medical Diagnosis Systems play a vital role in medical practice and are used by medical practitioners for diagnosis and treatment. In this system, a medical diagnosis system is presented for predicting the risk of cardiovascular disease. This system is built by combining the relative advantages of neural network and genetic algorithm. Artificial neural networks are particularly suited for complex classification problems. The weights of the neural network are determined using genetic algorithm because it finds acceptably good set of weights in less number of iterations. The dataset is used for training and testing. First, the dataset is pre-processed in order to make them suitable for training. Then, genetic based neural network is used for training the dataset. The final weights of the neural network are stored in the weight base and are used for predicting the risk of cardiovascular disease. Later, the system generates the charts which helps the people to know what further precautions are to be taken or followed after the prediction of the disease. The chart is generated on the basis of the results which is predicted after testing of the dataset.