Health Professions
2 years ago

Novel Random Forest Algorithm Outperforms Logistic Regression in Heart Disease Prediction.

CARDIOMETRY
Classification and Prediction of Heart Disease using Novel Random Forest Algorithm by Comparing Logistic Regression for Obtaining Better Accuracy
T. Poojitha, R. Mahaveerakannan

Paper Summary

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Novel Random Forest Algorithm Outperforms Logistic Regression in Heart Disease Prediction.

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Logistic Regression Outperforms Random Forest in Predicting Cardiovascular Disease Accuracy

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Heart attacks are often caused by blockages in the heart's blood vessels. This article compares two methods, Random Forest and Logistic Regression, to predict heart disease accurately. They used data from 143 samples and found that Random Forest had a higher accuracy rate of 90.16% compared to Logistic Regression at 85.25%. The study suggests that Random Forest is better for predicting heart disease.