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A Novel Method for Heart Disease Prediction and Prognosis using Data Mining Algorithms

K. Koperski, J. Adhikary, D. Delen

Abstract


The application of data mining techniques in various sectors like e-commerce, economics has led to its application in other sectors like healthcare, seismic analysis, weather forecasting etc., Among these sectors, healthcare gains prominence. The healthcare sector has commonly abundant data, but not all the data are properly utilized for uncovering hidden patterns and to help in effective decision making. It is mandatory to find out the hidden patterns and relationships. Data mining's 'Modeling-Techniques' obviously help in this scenario. It used to Classification Modeling Techniques like Decision Trees, Naive Bayes and Neural Network, along with weighted Association's Apriori Algorithm and MAFIA Algorithm in predicting Cardio Vascular Disease. One can easily found the symptoms of CVD from a patient by using their data like age, sex, blood pressure, and blood sugar.


Keywords


Heart Disease Prediction, Decision Trees, Naive Bayes and Neural Network.

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References


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