Data mining is the computer based process of analyzing large sets of data and then extracting the meaningful patterns. Data mining tools predict future trends which allow business to make knowledge-driven decisions. Data mining tools can answer the business questions which take much time to resolve in real world. The huge amount of data generated for prediction of heart disease are too complex to be processed and analyzed by traditional methods. Data mining provides the methodology to transform these mounds of data into useful information for decision making. It takes less time for the prediction of the disease by using data mining techniques with more accuracy. In this paper we survey different papers in which one or more algorithms of data mining are used for the prediction of heart disease. In Some papers it is shown that a SVM provide effective and efficient accuracy as compared to other data mining techniques in the prediction of heart disease. Applying data mining techniques in case of heart disease treatment data can provide as reliable performance as that achieved in diagnosing heart disease.
Data mining, Heart disease, Data mining techniques.