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World J Gastroenterol. Dec 21, 2025; 31(47): 111900
Published online Dec 21, 2025. doi: 10.3748/wjg.v31.i47.111900
Artificial intelligence applications for managing metabolic dysfunction-associated steatotic liver disease: Current status and future prospects
Jian-Jun Lou, Jing Zeng
Jian-Jun Lou, Chronic Liver Disease Center, The Affiliated Yangming Hospital of Ningbo University (Yuyao People's Hospital), Ningbo 315400, Zhejiang Province, China
Jing Zeng, Department of Gastroenterology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200092, China
Author contributions: Lou JJ designed the overall concept and outline of the manuscript; Lou JJ and Zeng J contributed to this paper, the writing, and editing the manuscript.
Supported by Shanghai Pujiang Program, No. 24PJD071; National Natural Science Foundation of China, No. 82100605; and Star Program of Shanghai Jiao Tong University, No. YG2021QN54.
Conflict-of-interest statement: The authors declare no competing financial interests.
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/
Corresponding author: Jing Zeng, MD, Department of Gastroenterology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, No. 1665 Kongjiang Road, Shanghai 200092, China. zjupup@126.com
Received: July 14, 2025
Revised: October 7, 2025
Accepted: November 5, 2025
Published online: December 21, 2025
Processing time: 160 Days and 9.8 Hours
Core Tip

Core Tip: Artificial intelligence (AI) is rapidly advancing the management of metabolic dysfunction-associated steatotic liver disease (MASLD). Because AI can integrate imaging, multiomics, and electronic health record data, the use of AI enables earlier diagnosis, more accurate risk stratification, and personalized treatment. This mini-review summarizes recent progress and future directions for applying AI to improve MASLD care and outcomes.