Prediction of Heart Disease through Data mining Techniques – A survey

IJCSEC Front Page

Abstract:
Heart malfunction is the leading disease worldwide. The detection of risk factors and their progress is complicated. The doctors and experts are not available in proportion to the population. In order to assist the physicians by developing an intelligent frame work for diagnosing the disease in heart is one of the essential goals of the researchers. The improved decision tree as C 5.0 is used for the effective extraction of the feature from data set for analysis. Using techniques like Naive Bayes, Neural Network, KNN algorithm and Decision Trees - an Intelligent Heart Disease Prediction System is created. In this paper, the prediction is done accurately using the above mentioned algorithms.

Keywords: Improved decision tree - C 5.0,Naive Bayes, Neural Network, KNN Algorithm, Decision Trees, Heart Disease Prediction System.

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