arXiv:2607. 25348v1 Announce Type: cross Abstract: Chronic Kidney Disease (CKD), characterized by the gradual loss of kidney function, remains a significant public health challenge.
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arXiv:2501. 16388v3 Announce Type: replace Abstract: Background: Chronic kidney disease (CKD), a progressive disease with high morbidity and mortality, has become a significant global public health problem.
arXiv:2607. 11963v1 Announce Type: cross Abstract: The early detection of Chronic Kidney Disease using machine learning has attracted significant interest in healthcare-related computer science.
The study uses large-scale telehealth data and machine learning to classify self‑reported chronic kidney disease (CKD) status and identify key risk factors. A customized stacked ensemble model achieved balanced accuracy of 72.56–76.12% and AUROC of 79.59–82.29%. SHapley Additive exPlanations revealed that regular medical check‑ups, age, blood pressure, and mental health stress indicators are critical predictors of CKD.
arXiv:2511. 02340v3 Announce Type: replace Abstract: Chronic Kidney Disease (CKD) affects nearly 10\% of the global population and often progresses to end-stage renal failure.
arXiv:2608. 03498v1 Announce Type: new Abstract: Federated Learning (FL) enables collaborative model training across distributed healthcare institutions without centralising sensitive patient data.
arXiv:2509. 10517v3 Announce Type: replace Abstract: Machine learning can predict in-hospital mortality, but data privacy and the statistical heterogeneity of clinical data hamper its use.