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Articles Published Processes
8/6/2026 7:34:31 AM | Browse: 0 | Download: 0
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Received |
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2026-05-28 07:12 |
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Peer-Review Started |
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2026-05-28 07:15 |
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First Decision by Editorial Office Director |
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2026-06-10 02:54 |
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Return for Revision |
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2026-06-10 02:54 |
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Revised |
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2026-06-12 11:15 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2026-06-30 02:41 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-06-30 06:29 |
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Articles in Press |
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2026-06-30 06:29 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-07-29 06:38 |
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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: http://creativecommons.org/Licenses/by-nc/4.0/ |
| 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 |
Systematic Reviews |
| Article Title |
Artificial intelligence and machine learning applications in abdominal tuberculosis diagnosis: A scoping review and translational roadmap
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Kumar Kaushik, Jyoti Pathania, Pritish Kumar Singh, Monika Dinkar and Vanya Pathania |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Jyoti Pathania, Full Professor, Head, MD, Department of Anesthesia, Rohilkhand Medical College and Hospital, Pilbhit Bypass Road, Bareilly 243006, Uttar Pradesh, India. pathaniajyoti7@gmail.com |
| Key Words |
Abdominal tuberculosis; Artificial intelligence; Machine learning; Radiomics; Deep learning; Scoping review; Translational roadmap; Crohn disease |
| Core Tip |
This is the first dedicated Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews-compliant scoping review of artificial intelligence and machine learning for abdominal tuberculosis diagnosis and differential diagnosis. It demonstrates high accuracy of radiomics, endoscopic convolutional neural networks, and multimodal models in differentiating abdominal tuberculosis from Crohn’s disease and other mimics, yet reveals a complete absence of management-focused artificial intelligence applications, and predominance of composite reference standards. The proposed four-phase roadmap provides a practical, equity-centered pathway from retrospective evidence to real-world deployment, prioritizing microbiological reference standards, bias audits, infrastructure-appropriate tools, and explicit integration with existing hierarchical diagnostic criteria to reduce diagnostic delays and unnecessary interventions in high-burden settings. |
| Publish Date |
2026-08-06 07:34 |
| Citation |
Kaushik K, Pathania J, Singh PK, Dinkar M, Pathania V. Artificial intelligence and machine learning applications in abdominal tuberculosis diagnosis: A scoping review and translational roadmap. Artif Intell Gastroenterol 2026; 7(2): 123751
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| URL |
https://www.wjgnet.com/2644-3236/full/v7/i2/123751.htm |
| DOI |
https://doi.org/10.35712/aig.123751 |
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