PREDICTIVE ANALYSIS OF DISEASE USING A-PRIORI AND K- MEAN TECHNIQUE
Disease prognostication is one of the most important issues that we are facing today. A large number of patients struggle for their check up even when it concerns of predictive diseases like heart attack possibilities, kidney damage and possibilities of lung problem. This motivates us to develop a hybrid algorithm which uses K-means and A-priori for data mining into large volumes of data and extract information that can be converted to useful knowledge and overall predict a patient for their chances of disease using a console. This console is developed with both algorithms working at back-end. This research paper is mainly focused on predicting lung and heart disease. Experimental results will show that many of the rules help in the best prediction of lung and heart disease, which even help doctors in their diagnostic decisions.
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