DETECTION OF HEART DISEASES USING DATA MINING TECHNIQUES

Data mining is the very apt technology, which includes the process of mining actionable information from huge dataset, which is used to analyze large masses of data and derive patterns or statistics that can be converted to knowledgeable implementation. Medical data mining has a great potential for deriving the hidden patterns in the data sets of medical industry. The derived patterns can be utilized to do clinical diagnosis. These data need to be collected in a standardized form. From the medical profiles fourteen attributes are extracted such as age, sex, blood pressure and blood sugar etc. can predict the likelihood of patient getting heart disease. These attributes are fed in to ID3 Algorithm and CART algorithm or Decision tree classification in heart disease prediction, applying the data mining technique to heart disease prediction; it could give a reliable performance that might result in diagnosing heart disease. By this medical industries could offer better diagnosis and treatment of the patient to attain a good quality of services. The main advantages of this paper are: early detection of heart disease ,providing measures for diagnosis and proving the efficiencies of ID3 and CART algorithms.