Genetic Neural Approach for Heart Disease Prediction

Data mining techniques are used to explore, analyze and extract data using complex algorithms in order to discover unknown patterns in the process of knowledge discovery. Heart disease is a major life threatening disease that cause to death and it has a serious long term disability. The time taken to recover from heart disease depends on patient’s severity. Heart disease diagnosis is complex task which requires much experience and knowledge. Nowadays, health care industry contain huge amount of health care data, which contain hidden information. Advanced data mining techniques along with computer generated information are used for appropriate results. Neural Network is widely used tool for predicting heart diseases diagnosis. A Heart Disease Prediction System is developed using Neural Network and Genetic Algorithm. This system calculates the number of hidden nodes for neural network which train the network with proper selection of neural network architecture and uses the global optimization of genetic algorithm for initialization of neural network. For prediction, the system uses 12 parameters such as sex, age, blood cholesterol etc. From the result, it is found that genetic neural approach predicts the heart disease upto 98% accuracy.