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12/17/2021 9:17:58 AM | Browse: 264 | Download: 398
Publication Name World Journal of Gastroenterology
Manuscript ID 66030
Country/Territory 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 Company 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
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