A SYSTEM FOR HEART DISEASE PREDICTION USING DATA MINING TECHNIQUES - Minal Zope; Sagar Birje; Lijo Johns; Amit Vasudevan (International Journal of Innovations in Engineering Research and Technology, 2021)
The diagnosis of heart disease is most complicated and tedious task in the field of medical science. Thus there is a need for development, a support system that will help medical practitioners to detect heart disease of a patient. Heart disease is something that cannot be detected by physical observation, but by analyzing different constraints that is associated with this disease.Thediagnosis depends on the careful analysis of different clinical and pathological data of the patient by medical experts, which is a complicated process. We propose efficient algorithm hybrid with ANN (Artificial Neural Network) and K-mean technique approach for heart disease prediction.The main objective of our model is to develop a prototype which can determine and extract known knowledge related with heart disease from the past heart disease database record. After implementingit and comparing with other techniques which have been used previously, our prediction came out to be around 87.35% which isway better compared withother techniques.