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Articles Published Processes
11/3/2026 3:34:10 AM | Browse: 1 | Download: 7
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Received |
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2026-06-15 02:10 |
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Peer-Review Started |
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2026-06-15 02:11 |
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First Decision by Editorial Office Director |
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Return for Revision |
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2026-07-22 08:52 |
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Revised |
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2026-08-04 11:50 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2026-09-09 02:32 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-09-09 10:23 |
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Articles in Press |
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2026-09-09 10:23 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-11-02 00:39 |
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Publish the Manuscript Online |
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2026-11-03 03:34 |
| ISSN |
2644-3236 (online) |
| Open Access |
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 |
Minireviews |
| Article Title |
Artificial intelligence in metabolic dysfunction-associated steatotic liver disease: A short narrative review of diagnostic and therapeutic implications
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Mona Mohamed Ibrahim Abdalla, Fabian Davamani and Nabil Eid |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Nabil Eid, Associate Professor, MD, PhD, Department of Human Biology, School of Medicine, IMU University, Bukit Jalil, Kuala Lumpur 57000, Malaysia. nabilsaleheid@imu.edu.my |
| Key Words |
Metabolic dysfunction-associated steatotic liver disease; Artificial intelligence; Machine learning; Liver fibrosis; Digital pathology; Precision hepatology |
| Core Tip |
Artificial intelligence (AI) can integrate clinical records, radiological imaging, digital histology, and molecular data to support metabolic dysfunction-associated steatotic liver disease detection and risk stratification. Evidence is strongest for retrospective identification, imaging-based classification, and reproducible histological quantification. In contrast, AI-guided treatment selection, lifestyle personalization, and therapeutic monitoring remain investigational. This review distinguishes clinically proximate applications from exploratory and preclinical uses and identifies the validation, fairness, implementation, and outcome requirements for responsible clinical translation. |
| Publish Date |
2026-11-03 03:34 |
| Citation |
Abdalla MMI, Davamani F, Eid N. Artificial intelligence in metabolic dysfunction-associated steatotic liver disease: A short narrative review of diagnostic and therapeutic implications. Artif Intell Gastroenterol 2026; 7(3): 124329
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| URL |
https://www.wjgnet.com/2644-3236/full/v7/i3/124329.htm |
| DOI |
https://doi.org/10.35712/aig.124329 |
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.
