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AI-Powered Heart Disease Prediction Boosts Survival Rates by 5%

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Performance Analysis of Heart Disease Prediction System using Novel Random Forest Over Naive Bayes Algorithm with an Improved Accuracy Rate
T. Poojitha, R. Mahaveerakannan

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The main goal of the study was to predict heart disease accurately using AI algorithms. The researchers compared the performance of a new method called Random Forest with a traditional method called Naive Bayes. They used data from 1402 samples and found that Random Forest had a higher accuracy rate of 90.16% compared to Naive Bayes at 85.25%. This suggests that Random Forest is better at predicting heart disease than Naive Bayes.