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What is Heart Disease Prediction: PSO-MRF Method about?

The paper presents a novel approach for predicting heart disease by combining particle swarm optimization (PSO) with a modified random forest (MRF) algorithm, referred to as PSO-MRF. This method aims to enhance feature selection and optimize model parameters, demonstrating superior performance compared to traditional random forest and other classifiers using the UCI heart disease dataset. The findings suggest that the PSO-MRF model can significantly aid in the diagnosis and treatment of heart disease, impro

Author

IAES IJAI

Language

EN