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Articles Published Processes
11/3/2026 3:34:08 AM | Browse: 1 | Download: 7
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Received |
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2026-07-07 08:15 |
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Peer-Review Started |
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2026-07-07 08:16 |
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First Decision by Editorial Office Director |
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Return for Revision |
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2026-08-04 08:54 |
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Revised |
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2026-08-14 11:13 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2026-10-15 03:35 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-10-16 09:22 |
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Articles in Press |
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2026-10-16 09:22 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-10-21 06:50 |
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Publish the Manuscript Online |
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2026-11-03 03:34 |
| ISSN |
2644-3236 (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 |
Meta-Analysis |
| Article Title |
Predicting pathological complete response to neoadjuvant chemoradiotherapy in rectal cancer via artificial intelligence: A systematic review and meta-analysis
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Felix Pius Omullo, Thomas Kimanzi Kitheghe, Ismail Abdi Sheikh, Abel Mwangi Gakuya, Joshua Macharia Gitumu, Mohamed Ahmed Shiekh, Wilson Owuor Agai, Wendy Bitengo Orenge and Harambee Moses Gogo |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Felix Pius Omullo, MD, Senior Researcher, Department of Clinical Research, St. Teresa Hospital, Off Kikuyu Thogoto Road, Kikuyu 1370, Kiambu, Kenya. piuskirasia@gmail.com |
| Key Words |
Locally advanced rectal cancer; Neoadjuvant chemoradiotherapy; Pathological complete response; Artificial intelligence; Machine learning; Deep learning; Radiomics; Diagnostic accuracy; Magnetic resonance imaging; Meta-analysis |
| Core Tip |
Artificial intelligence (AI) and radiomics models demonstrate pooled accuracy of 0.889 with low between-study heterogeneity (I² = 11.3%). Performance was consistent across internal, temporal, and external validation cohorts (area under the curve: 0.877-0.901) and between low and high risk-of-bias studies. However, the positive predictive value (54.4%) remains insufficient for artificial intelligence to confirm pathological complete response independently. Prospective validation with standardized reporting is required before implementation. AI should be integrated with, rather than replace, multidisciplinary assessment. |
| Publish Date |
2026-11-03 03:34 |
| Citation |
Omullo FP, Kitheghe TK, Sheikh IA, Gakuya AM, Gitumu JM, Shiekh MA, Agai WO, Orenge WB, Gogo HM. Predicting pathological complete response to neoadjuvant chemoradiotherapy in rectal cancer via artificial intelligence: A systematic review and meta-analysis. Artif Intell Gastroenterol 2026; 7(3): 125015
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| URL |
https://www.wjgnet.com/2644-3236/full/v7/i3/125015.htm |
| DOI |
https://doi.org/10.35712/aig.125015 |
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.
