Can I read Machine Learning for Heart Disease Prediction on EtoBox?
Machine Learning for Heart Disease Prediction by M Gowda is a document available to read on EtoBox.
What is Machine Learning for Heart Disease Prediction about?
This study evaluates various machine learning algorithms for predicting heart disease using a dataset of 1,000 patients. The Random Forest algorithm outperformed others with an accuracy of 93.2% and an AUC-ROC value of 0.96, while Decision Trees followed with 91.5% accuracy. The findings highlight the potential of machine learning in enhancing clinical decision support systems for heart disease.
- Author
- M Gowda
- Language
- EN