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Machine Learning for Diabetic Heart Disease by IJPHS is a document available to read on EtoBox.

What is Machine Learning for Diabetic Heart Disease about?

This study evaluates cardiovascular disease risk in diabetic patients using various machine learning techniques, including decision trees, AdaBoost, support vector machines, and artificial neural networks. The proposed model incorporates particle swarm optimization and k-nearest neighbors for feature selection and aims to improve prediction accuracy compared to existing methods. The research highlights the importance of early detection and personalized treatment in managing heart disease, which is a leading

Author

IJPHS

Language

EN