Publication Name	World Journal of Nephrology
Manuscript ID	117719
Country	Egypt

Category	Urology & Nephrology
Manuscript Type	Review
Article Title	Artificial intelligence in chronic kidney disease: Early detection, risk prediction, and personalized treatment strategies
Manuscript Source	Invited Manuscript
All Author List	Kirolos Eskandar
Funding Agency and Grant Number
Corresponding Author	Kirolos Eskandar, MD, Researcher, Medicine and Surgery, Helwan University, Al Masaken Al Iqtisadeyah, Helwan, Cairo Governorate 4034572, Giza 11795, Al Jīzah, Egypt. kirolos210575@med.helwan.edu.eg
Key Words	Machine learning; Deep learning; Precision nephrology; Clinical decision support; Multimodal data integration
Core Tip	Artificial intelligence (AI) holds significant promise for transforming chronic kidney disease (CKD) care by integrating longitudinal, high-dimensional, and multimodal clinical data to support earlier detection, improved risk stratification, and personalized management. This review synthesizes recent evidence on AI applications across the CKD continuum, including early detection, risk prediction, personalized treatment, complication management, dialysis, and kidney transplantation. Beyond reporting model performance, it critically examines validation quality, calibration, explainability, equity, and real-world implementation barriers, highlighting the persistent gap between methodological innovation and routine clinical deployment. The review outlines key priorities required to translate AI tools into safe, equitable, and clinically meaningful CKD care.
Citation	Eskandar K. Artificial intelligence in chronic kidney disease: Early detection, risk prediction, and personalized treatment strategies. World J Nephrol 2026; In press

Received	2025-12-16 01:35
Peer-Review Started	2025-12-16 01:35
First Decision by Editorial Office Director	2026-01-16 06:56
Return for Revision	2026-01-16 06:56
Revised	2026-01-18 22:11
Publication Fee Transferred
Second Decision by Editor	2026-02-09 02:42
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director	2026-02-09 08:16
Articles in Press	2026-02-09 08:16
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	2220-6124 (online)
Open Access	This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
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