Publication Name	World Journal of Gastroenterology
Manuscript ID	66030
Country	Canada

Received	2021-03-19 14:55
Peer-Review Started	2021-03-19 14:58
To Make the First Decision
Return for Revision	2021-08-09 18:04
Revised	2021-08-22 15:59
Second Decision	2021-12-06 03:31
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2021-12-08 05:57
Articles in Press	2021-12-08 05:57
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2021-12-15 02:14
Publish the Manuscript Online	2021-12-17 08:56

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/
Copyright	© The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
Article Reprints	For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
Permissions	For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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	Minireviews
Article Title	Artificial intelligence-assisted colonoscopy: A review of current state of practice and research
Manuscript Source	Invited Manuscript
All Author List	Mahsa Taghiakbari, Yuichi Mori and Daniel von Renteln
ORCID	Author(s) ORCID Number Mahsa Taghiakbari http://orcid.org/0000-0001-6011-3400 Yuichi Mori http://orcid.org/0000-0003-2262-0334 Daniel von Renteln http://orcid.org/0000-0002-6125-0068
Funding Agency and Grant Number
Corresponding Author	Daniel von Renteln, MD, Associate Professor, Department of Gastroenterology, CRCHUM, 900 Rue Saint Denis, Montreal H2X 0A9, Quebec, Canada. danielrenteln@gmail.com
Key Words	Colonoscopy; Adenoma; Artificial intelligence; Computational intelligence; Endoscopy; Surveillance
Core Tip	Artificial intelligence (AI)-assisted decision support systems for endoscopy have shown promising results for the detection and classification of colorectal lesions. However, their integration into clinical practice is currently limited by the lack of design, validation, and testing under real-life clinical conditions. Further work is required to address the challenges of AI integration, to navigate the regulatory approval process, and to support physicians and patients on their journey to accepting the technology by providing strong evidence of accuracy and safety. This article describes the current state of AI integration into colonoscopy practice and offers suggestions for future research.
Publish Date	2021-12-17 08:56
Citation	Taghiakbari M, Mori Y, von Renteln D. Artificial intelligence-assisted colonoscopy: A review of current state of practice and research. World J Gastroenterol 2021; 27(47): 8103-8122
URL	https://www.wjgnet.com/1007-9327/full/v27/i47/8103.htm
DOI	https://dx.doi.org/10.3748/wjg.v27.i47.8103

Full Article (PDF)	WJG-27-8103.pdf
Full Article (Word)	WJG-27-8103.docx
Manuscript File	66030_Auto_Edited.docx
Answering Reviewers	66030-Answering reviewers.pdf
Audio Core Tip	66030-Audio core tip.m4a
Conflict-of-Interest Disclosure Form	66030-Conflict-of-interest statement.pdf
Copyright License Agreement	66030-Copyright license agreement.pdf
Peer-review Report	66030-Peer-review(s).pdf
Scientific Misconduct Check	66030-Bing-Fan JR-2.png
Scientific Editor Work List	66030-Scientific editor work list.pdf
CrossCheck Report	66030-CrossCheck report.pdf
CrossCheck Report	66030-CrossCheck.png