Breaking new ground in cardiovascular heart disease Diagnosis K-RFC: An integrated learning approach with K-means clustering and Random Forest classifier
Ahmed Hamza Osman,
Ashraf Osman Ibrahim,
Abeer Alsadoon
et al.
Abstract:<abstract>
<p>The ability to accurately anticipate heart failure risks in a timely manner is essential because heart failure has been identified as one of the leading causes of death. In this paper, we propose a novel method for identifying cardiovascular heart disease by utilizing a K-means clustering and Random Forest classifier combination. Based on their clinical and demographic traits, patients were classified into either healthy or diseased groups using the Random Forest classifier after bei… Show more
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