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Articles Published Processes
5/26/2026 3:52:08 AM | Browse: 2 | Download: 0
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Received |
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2025-12-01 00:42 |
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Peer-Review Started |
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2025-12-01 00:42 |
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First Decision by Editorial Office Director |
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2025-12-25 08:24 |
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Return for Revision |
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2025-12-25 08:24 |
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Revised |
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2026-01-04 21:49 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2026-01-29 02:33 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-01-29 08:06 |
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Articles in Press |
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2026-01-29 08:06 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-05-14 06:55 |
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Publish the Manuscript Online |
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2026-05-26 03:52 |
| ISSN |
1948-5182 (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/ |
| Copyright |
© The Author(s) 2026. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Gastroenterology & Hepatology |
| Manuscript Type |
Review |
| Article Title |
Artificial intelligence and machine learning in hepatology: Revolutionizing diagnosis and treatment
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Mohammed OK Elsayed and Ahmed Y Elshabrawi |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Mohammed OK Elsayed, FRCP, MD, Professor, Department of Gastroenterology, South Tees Hospitals NHS Foundation Trust, The James Cook University Hospital, Marton Road, Middlesbrough TS4 3BW, United Kingdom. mohammed.omar@nhs.net |
| Key Words |
Artificial intelligence; Machine learning; Deep learning; Liver transplant; Hepatocellular carcinoma; Cirrhosis |
| Core Tip |
Artificial intelligence (AI) is transforming hepatology by improving disease detection, prognostication, and treatment planning. Machine learning and deep learning models outperform traditional tools by integrating imaging, laboratory, histological, and clinical data. However, challenges, including dataset bias, lack of interpretability, and limited prospective validation, still hinder routine clinical use. This review outlines current applications, limitations, and future directions, highlighting how AI could support more precise, equitable, and personalized liver care. |
| Publish Date |
2026-05-26 03:52 |
| Citation |
Elsayed MO, Elshabrawi AY. Artificial intelligence and machine learning in hepatology: Revolutionizing diagnosis and treatment. World J Hepatol 2026; 18(5): 117141 |
| URL |
https://www.wjgnet.com/1948-5182/full/v18/i5/117141.htm |
| DOI |
https://dx.doi.org/10.4254/wjh.v18.i5.117141 |
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