Development of risk models for early detection and prediction of chronic kidney disease in clinical settings

Abstract Chronic kidney disease (CKD) imposes a high burden with high mortality and morbidity rates. Early detection of CKD is imperative in preventing the adverse outcomes attributed to the later stages. Therefore, this study aims to utilize machine learning techniques to predict CKD at early stage...

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Bibliographic Details
Main Authors: Pegah Bahrami, Davoud Tanbakuchi, Monavar Afzalaghaee, Majid Ghayour-Mobarhan, Habibollah Esmaily
Format: Article
Language:English
Published: Nature Portfolio 2024-12-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-024-83973-5
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