Copyright
©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Dec 21, 2021; 27(47): 8103-8122
Published online Dec 21, 2021. doi: 10.3748/wjg.v27.i47.8103
Published online Dec 21, 2021. doi: 10.3748/wjg.v27.i47.8103
Artificial intelligence-assisted colonoscopy: A review of current state of practice and research
Mahsa Taghiakbari, Daniel von Renteln, Department of Gastroenterology, CRCHUM, Montreal H2X 0A9, Quebec, Canada
Yuichi Mori, Clinical Effectiveness Research Group, University of Oslo, Oslo 0450, Norway
Yuichi Mori, Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama 224-8503, Japan
Author contributions: Taghiakbari M drafted the manuscript under the supervision of von Renteln D; Mori Y and von Renteln D performed the critical revision of the manuscript for important intellectual content.
Conflict-of-interest statement: Mahsa Taghiakbari has no conflicts of interest relevant to this paper to disclose. Yuichi Mori is a consultant for the Olympus corporation and receives a speaking fee from the same corporation. Yuichi Mori has an ownership interest in Cybernet System Corporation. Daniel von Renteln is supported by the “Fonds de Recherche du Québec Santé” career development award and has received research funding from ERBE, Ventage, Pendopharm, and Pentax; he is also a consultant for Boston Scientific and Pendopharm.
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/
Corresponding author: Daniel von Renteln, MD, Associate Professor, Department of Gastroenterology, CRCHUM, 900 Rue Saint Denis, Montreal H2X 0A9, Quebec, Canada.
Received: March 19, 2021
Peer-review started: March 19, 2021
First decision: August 9, 2021
Revised: August 22, 2021
Accepted: December 3, 2021
Article in press: December 7, 2021
Published online: December 21, 2021
Processing time: 272 Days and 18 Hours
Peer-review started: March 19, 2021
First decision: August 9, 2021
Revised: August 22, 2021
Accepted: December 3, 2021
Article in press: December 7, 2021
Published online: December 21, 2021
Processing time: 272 Days and 18 Hours
Core Tip
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.