ABSTRACT
Data mining techniques have been mostly used in medical area for prediction and diagnosis of various diseases. These techniques discover the hidden pattern and relationship in medical data and therefore have been very important in designing clinical support. Now a day's data mining techniques are widely used in diagnosis of heart disease because of increasing death rate worldwide. The reason of this may be the complex and expensive tests conducted in labs to predict the heart disease. Systems based on these risk factors not only bene?t healthcare professionals, but warn them of the potential presence of heart disease even before a patient is admitted to the hospital or undergoes an expensive medical examination. This in order to reduce the risk of this disease a better approach would to identify risk factor the result in heart disease. This study is an effort in this direction. This approach to predict the heart disease in early stage is developed in present study by analyzing risk factors. This technique developed weighted gain decision tree predicts the risk of heart disease with an accuracy of 90%