Model validation demonstrates accurate forecasting of disease progression in patients with stage 3-5 chronic kidney disease, highlighting machine learning utility for clinical decision-making.
The use of tools that allow estimation of the probability of progression of chronic kidney disease (CKD) to advanced stages has not yet achieved significant practical importance in clinical setting. This study aimed to develop and validate a machine learning-based model for predicting the need for renal replacement therapy (RRT) and disease progression for patients with stage 3-5 CKD.
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Isaza-Ruget et al. (2024) studied this question.
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