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Hybrid ML Algorithms for Heart Disease Prediction by ewuiplkw phuvdj is a document available to read on EtoBox.

This document discusses several studies that have used machine learning techniques to predict cardiovascular disease. It begins by introducing cardiovascular disease as a major global health issue and the use of machine learning for disease prediction. It then reviews past studies that have used techniques like decision trees, genetic algorithms, naive Bayes and k-nearest neighbor algorithms for prediction. The document proposes using a hybrid random forest and linear model technique to improve prediction a

Author

ewuiplkw phuvdj

Language

EN