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Artif Intell Gastrointest Endosc. Aug 28, 2021; 2(4): 157-167
Published online Aug 28, 2021. doi: 10.37126/aige.v2.i4.157
Artificial intelligence and colonoscopy − enhancements and improvements
Byung Soo Yoo, Steve M D'Souza, Kevin Houston, Ankit Patel, James Lau, Alsiddig Elmahdi, Parth J Parekh, David Johnson
Byung Soo Yoo, Steve M D'Souza, Kevin Houston, Ankit Patel, James Lau, Alsiddig Elmahdi, Department of Medicine, Eastern Virginia Medical School, Norfolk, VA 23507, United States
Parth J Parekh, David Johnson, Division of Gastroenterology, Department of Internal Medicine, Eastern Virginia Medical School, Norfolk, VA 23505, United States
Author contributions: Johnson DA, Parekh PJ, D'Souza SM and Yoo BS contributed to the construction of the project; all authors wrote and edited the manuscript.
Conflict-of-interest statement: Authors have nothing to disclose.
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: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: David Johnson, MD MACG, FASGE, MACP, Professor of Medicine, Chief, Division of Gastroenterology Department of Internal Medicine, Eastern Virginia Medical School, 886 Kempsville Road Suite 114, Norfolk, VA 23505, United States. dajevms@aol.com
Received: June 5, 2021
Peer-review started: June 5, 2021
First decision: June 18, 2021
Revised: June 21, 2021
Accepted: July 23, 2021
Article in press: July 23, 2021
Published online: August 28, 2021
Core Tip

Core Tip: The application of artificial intelligence (AI) in medicine and gastroenterology has demonstrated to date, broad utility in both disease diagnostics and management. The utility of AI in colonoscopy has recently demonstrated enhanced polyp detection and characterization, assessment for mucosal healing and identification of dysplasia associated with inflammatory bowel disease, as well as assessment of the quality of bowel preparation for colonoscopy.