Artificial intelligence in chronic kidney disease: Early detection, risk prediction, and personalized treatment strategies

doi:10.5527/wjn.v15.i2.117719

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World Journal of Nephrology

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2220-6124

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.

World J Nephrol. Jun 25, 2026; 15(2): 117719
Published online Jun 25, 2026. doi: 10.5527/wjn.v15.i2.117719

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Figure 4 Closed-loop artificial intelligence-enabled management of chronic kidney disease complications. Conceptual feedback loop illustrating continuous data acquisition, prediction, intervention, and response updating to support dynamic and adaptive management of chronic kidney disease-related complications using artificial intelligence. AI: Artificial intelligence; IDH: Intradialytic hypotension; PTH: Parathyroid hormone; CKD-MBD: CKD-mineral and bone disorder; ESA: Erythropoiesis-stimulating agent; UF: Ultrafiltration.

Citation: Eskandar K. Artificial intelligence in chronic kidney disease: Early detection, risk prediction, and personalized treatment strategies. World J Nephrol 2026; 15(2): 117719
URL: https://www.wjgnet.com/2220-6124/full/v15/i2/117719.htm
DOI: https://dx.doi.org/10.5527/wjn.v15.i2.117719

Eskandar K. Artificial intelligence in chronic kidney disease: Early detection, risk prediction, and personalized treatment strategies. World J Nephrol 2026; 15(2): 117719 [PMID: 42395685 DOI: 10.5527/wjn.v15.i2.117719]

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