Heart Disease Risk Prediction Using Machine Learning Classifiers with Attribute Evaluators
Cardiovascular diseases (CVDs) kill about 20.5 million people every year. Early prediction can help people to change their lifestyles and to ensure proper medical treatment if necessary. In this research, ten machine learning (ML) classifiers from different categories, such as Bayes, functions, lazy...
Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-09-01
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Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/11/18/8352 |