Retrospective study reveals accurate mortality risk prediction in maintenance hemodialysis patients, highlighting critical clinical factors identified via explainable machine learning.
The K-Nearest Neighbor model demonstrated high efficacy in predicting mortality risk among hemodialysis patients. SHAP analysis highlighted critical risk factors. While these findings show promise for future clinical research, they should be interpreted with caution due to the study's retrospective design and the need for external validation.
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Shu et al. (2025) studied this question.
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