Publication Name	World Journal of Gastroenterology
Manuscript ID	111499
Country	Greece

Received	2025-07-01 09:19
Peer-Review Started	2025-07-01 09:19
To Make the First Decision
Return for Revision	2025-07-28 09:01
Revised	2025-08-09 14:40
Second Decision	2025-09-18 02:42
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2025-09-18 03:29
Articles in Press	2025-09-18 03:29
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2025-10-21 01:48
Publish the Manuscript Online	2025-10-27 08:08

ISSN	1007-9327 (print) and 2219-2840 (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/
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Category	Gastroenterology & Hepatology
Manuscript Type	Review
Article Title	Artificial intelligence in colonoscopy: Enhancing quality indicators for optimal patient outcomes
Manuscript Source	Invited Manuscript
All Author List	Konstantina Dimopoulou, Marianna Spinou, Alexandros Ioannou, Eleni Nakou, Petros Zormpas and George Tribonias
Funding Agency and Grant Number
Corresponding Author	Konstantina Dimopoulou, Consultant, MD, PhD, Department of Gastroenterology, Red Cross Hospital, 1, Athanasaki str, Athens 11526, Greece. conu_med@hotmail.com
Key Words	Artificial intelligence; Colonoscopy; Outcome; Quality indicators; Detection rates
Core Tip	Artificial intelligence (AI) has emerged as a breakthrough innovation in modern colonoscopy, offering significant improvements in key quality indicators, including adenoma detection rate, polyp detection rate, adenoma miss rate, bowel preparation assessment, withdrawal time, and cecal intubation recognition. By optimizing lesion characterization, supporting optical diagnosis and assisting in invasion depth prediction, AI may lead to early diagnosis and prevention of colorectal cancer. This review summarizes the current evidence on the application of AI in key colonoscopy quality indicators, highlighting its role in standardizing practice, improving patient outcomes, and advancing personalized care while also addressing the challenges of training, cost-effectiveness, and ethical considerations.
Publish Date	2025-10-27 08:08
Citation	<p>Dimopoulou K, Spinou M, Ioannou A, Nakou E, Zormpas P, Tribonias G. Artificial intelligence in colonoscopy: Enhancing quality indicators for optimal patient outcomes. <i>World J Gastroenterol</i> 2025; 31(40): 111499</p>
URL	https://www.wjgnet.com/1007-9327/full/v31/i40/111499.htm
DOI	https://dx.doi.org/10.3748/wjg.v31.i40.111499

Full Article (PDF)	WJG-31-111499-with-cover.pdf
Manuscript File	111499_Auto_Edited_085854.docx
Answering Reviewers	111499-answering-reviewers.pdf
Audio Core Tip	111499-audio.mp3
Conflict-of-Interest Disclosure Form	111499-conflict-of-interest-statement.pdf
Copyright License Agreement	111499-copyright-assignment.pdf
Non-Native Speakers of English Editing Certificate	111499-non-native-speakers.pdf
Peer-review Report	111499-peer-reviews.pdf
Scientific Misconduct Check	111499-scientific-misconduct-check.png
Scientific Editor Work List	111499-scientific-editor-work-list.pdf
CrossCheck Report	111499-crosscheck-report.pdf