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Articles Published Processes
10/21/2026 2:09:37 AM | Browse: 1 | Download: 0
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Received |
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2026-06-29 09:43 |
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Peer-Review Started |
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2026-06-29 09:43 |
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First Decision by Editorial Office Director |
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Return for Revision |
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2026-07-28 07:09 |
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Revised |
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2026-08-05 08:45 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2026-09-17 02:42 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-09-17 09:38 |
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Articles in Press |
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2026-09-17 09:38 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-09-30 14:46 |
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Publish the Manuscript Online |
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2026-10-21 02:09 |
| ISSN |
1948-5182 (online) |
| Open Access |
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. |
| Copyright |
©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc. |
| 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 in autoimmune liver diseases: Diagnosis, risk stratification, and personalized care
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Ahmed Salman |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Ahmed Salman, FRACP, FRCP, Department of Internal Medicine, Kasr Alainy School of Medicine, 1 Al-Saray Street, Al-Manial, Cairo 11562, Egypt. awea844@gmail.com |
| Key Words |
Artificial intelligence; Machine learning; Deep learning; Autoimmune hepatitis; Primary biliary cholangitis; Primary sclerosing cholangitis; Autoimmune liver disease; Precision medicine; Digital pathology; Large language models |
| Core Tip |
Artificial intelligence can be used to quantify images and combine multimodal data in autoimmune liver disease; however, most models remain investigational. The best-supported evidence currently comes from externally validated differential diagnosis models for autoimmune hepatitis, established machine learning prognostic tools for primary sclerosing cholangitis, and treatment response models for primary biliary cholangitis. However, these tools require local validation and monitoring during clinical testing. Clinicians should seek calibration, comparison with current care, decision curve benefit, and subgroup performance; however, the area under the curve alone is insufficient. No current model supports autonomous diagnosis or changes in therapy or surveillance without guideline-based clinical judgment. |
| Publish Date |
2026-10-21 02:09 |
| Citation |
Salman A. Artificial intelligence in autoimmune liver diseases: Diagnosis, risk stratification, and personalized care. World J Hepatol 2026; 18(10): 124997
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| URL |
https://www.wjgnet.com/1948-5182/full/v18/i10/124997.htm |
| DOI |
https://doi.org/10.4254/wjh.124997 |
Copyright © 1993-2026 Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA. All rights reserved, including rights relating to text and data mining, AI training, and similar technologies. For open-access content, the applicable copyright and licensing terms govern.
