Dynamic survival prediction of end-stage kidney disease using random survival forests for competing risk analysis

Background and hypothesisA static predictive model relying solely on baseline clinicopathological data cannot capture the heterogeneity in predictor trajectories observed in the progression of chronic kidney disease (CKD). To address this, we developed and validated a dynamic survival prediction mod...

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Bibliographic Details
Main Authors: Daniel Christiadi, Kevin Chai, Aaron Chuah, Bronwyn Loong, Thomas D. Andrews, Aron Chakera, Giles Desmond Walters, Simon Hee-Tang Jiang
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-12-01
Series:Frontiers in Medicine
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Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2024.1428073/full
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