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8/6/2026 7:34:29 AM | Browse: 0 | Download: 0
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Received |
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2025-11-14 04:48 |
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Peer-Review Started |
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2025-11-14 04:48 |
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First Decision by Editorial Office Director |
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2025-11-26 09:23 |
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Return for Revision |
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2025-11-26 09:23 |
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Revised |
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2026-01-08 06:53 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2026-01-27 02:40 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-01-27 05:56 |
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Articles in Press |
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2026-01-27 05:56 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-02-09 00:54 |
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Publish the Manuscript Online |
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2026-08-06 07:34 |
| ISSN |
2644-3236 (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 |
Pathology |
| Manuscript Type |
Minireviews |
| Article Title |
Artificial intelligence in celiac disease pathology: From digital histomorphology to multi-modal integration
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Hakim Rahmoune, Nada Boutrid and Isra Benchoufi |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Hakim Rahmoune, Associate Professor, MD, PhD, LIRSSEI Research Laboratory, Faculty of Medicine, University of Setif-1, El Bez Campus, Setif 19000, Setif, Algeria. rahmounehakim@gmail.com |
| Key Words |
Celiac disease; Histopathology; Marsh classification; Flow cytometry; Artificial intelligence; Deep learning; Machine learning; Digital pathology |
| Core Tip |
Artificial intelligence (AI), particularly deep learning models, has advanced histopathological diagnosis of celiac disease (CD) by automating objective measurement of villous-crypt ratios, intraepithelial lymphocyte quantification, and Marsh classification. Novel multi-modal integration combining AI-histopathology with AI-analyzed flow cytometry data offers enhanced diagnostic accuracy and objectivity. Despite challenges in model interpretability and clinical workflow integration, AI demonstrates transformative potential in reducing inter-observer variability and improving CD diagnosis reproducibility and efficiency. |
| Publish Date |
2026-08-06 07:34 |
| Citation |
Rahmoune H, Boutrid N, Benchoufi I. Artificial intelligence in celiac disease pathology: From digital histomorphology to multi-modal integration. Artif Intell Gastroenterol 2026; 7(2): 116570
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| URL |
https://www.wjgnet.com/2644-3236/full/v7/i2/116570.htm |
| DOI |
https://doi.org/10.35712/aig.v7.i2.116570 |
All content on this site: Copyright © 1993-2026 Baishideng Publishing Group Inc, its licensors, and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For all open access content, the relevant licensing terms apply.
