Publication Name	Artificial Intelligence in Gastroenterology
Manuscript ID	125015
DOI	10.35712/aig.125015
Country	Kenya

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
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
Funding Agency and Grant Number
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.
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; In press DOI: https://doi.org/10.35712/aig.125015
PDF	125015-in-press.pdf

Received	2026-07-07 08:15
Peer-Review Started	2026-07-07 08:16
First Decision by Editorial Office Director
Return for Revision	2026-08-04 08:54
Revised	2026-08-14 11:13
Publication Fee Transferred
Second Decision by Editor	2026-10-15 03:35
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director	2026-10-16 09:22
Articles in Press	2026-10-16 09:22
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	2644-3236 (online)
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Copyright	©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc.
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