Publication Name	World Journal of Gastroenterology
Manuscript ID	111176
Country	China

Category	Gastroenterology & Hepatology
Manuscript Type	Review
Article Title	Artificial intelligence in hepatopathy diagnosis and treatment: Big data analytics, deep learning, and clinical prediction models
Manuscript Source	Invited Manuscript
All Author List	Jing-Ran Sun, Xiao-Ning Sun, Bing-Jiu Lu and Bao-Cheng Deng
Funding Agency and Grant Number	Funding Agency Grant Number Science Planning Project of Liaoning Province 2019JH2/10300031-05 National Natural Science Foundation of China 12171074
Corresponding Author	Bao-Cheng Deng, PhD, The Second Department of Infectious Diseases, The First Affiliated Hospital, China Medical University, No. 155 Nanjing North Street, Shenyang 110001, Liaoning Province, China. sydengbc@163.com
Key Words	Artificial intelligence; Hepatology; Liver disease diagnosis; Deep learning; Clinical prediction models
Core Tip	This review highlights how artificial intelligence is transforming hepatology by enabling early diagnosis, fibrosis staging, hepatocellular carcinoma detection, and personalized treatment. Key innovations include deep learning for imaging, multi-omics integration, and privacy-preserving federated learning. Explainable artificial intelligence builds clinician trust. Despite promising results, challenges like data heterogeneity, regulatory barriers, and limited real-time integration remain. Continued efforts in validation, ethical oversight, and user-centered design are essential for clinical adoption.
Citation	Sun JR, Sun XN, Lu BJ, Deng BC. Artificial intelligence in hepatopathy diagnosis and treatment: Big data analytics, deep learning, and clinical prediction models. World J Gastroenterol 2025; In press

Received	2025-06-30 09:27
Peer-Review Started	2025-06-30 09:27
To Make the First Decision
Return for Revision	2025-08-06 11:45
Revised	2025-08-31 08:28
Second Decision	2025-10-21 02:53
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2025-10-21 06:41
Articles in Press	2025-10-21 06:41
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	1007-9327 (print) and 2219-2840 (online)
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