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What is Heart Disease Prediction with Data Mining about?

This paper explores the use of data mining techniques, specifically Artificial Neural Networks (ANN), Decision Tree, and Naive Bayes, for predicting heart disease based on medical data. The study concludes that ANN outperforms the other methods with an accuracy of 100%, while Decision Tree and Naive Bayes achieved accuracies of 88.02% and 85.86%, respectively. The research emphasizes the potential of these techniques to streamline heart disease diagnosis, reducing reliance on extensive medical tests.

Author

HANISHA SAALIH

Language

EN