Galati JS, Duve RJ, O'Mara M, Gross SA. Artificial intelligence in gastroenterology: A narrative review. Artif Intell Gastroenterol 2022; 3(5): 117-141 [DOI: 10.35712/aig.v3.i5.117]
Corresponding Author of This Article
Jonathan S Galati, MD, Department of Medicine, NYU Langone Health, 550 First Avenue, New York, NY 10016, United States. jonathan.galati@nyulangone.org
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Review
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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/
Artif Intell Gastroenterol. Dec 28, 2022; 3(5): 117-141 Published online Dec 28, 2022. doi: 10.35712/aig.v3.i5.117
Artificial intelligence in gastroenterology: A narrative review
Jonathan S Galati, Robert J Duve, Matthew O'Mara, Seth A Gross
Jonathan S Galati, Department of Medicine, NYU Langone Health, New York, NY 10016, United States
Robert J Duve, Department of Internal Medicine, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY 14203, United States
Matthew O'Mara, Seth A Gross, Division of Gastroenterology, NYU Langone Health, New York, NY 10016, United States
Author contributions: Galati JS, Gross SA contributed to manuscript concept and design; Galati JS, Duve RJ, O'Mara M contributed to obtaining and interpreting literary sources, drafting of manuscript; Galati JS, Duve RJ, O'Mara M, Gross SA contributed to revision of manuscript; All authors read and approved the final version of the manuscript.
Conflict-of-interest statement: All the authors declare that they have no conflict of interest.
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: Jonathan S Galati, MD, Department of Medicine, NYU Langone Health, 550 First Avenue, New York, NY 10016, United States. jonathan.galati@nyulangone.org
Received: October 9, 2022 Peer-review started: October 9, 2022 First decision: October 29, 2022 Revised: November 21, 2022 Accepted: December 21, 2022 Article in press: December 21, 2022 Published online: December 28, 2022 Processing time: 79 Days and 8.7 Hours
Abstract
Artificial intelligence (AI) is a complex concept, broadly defined in medicine as the development of computer systems to perform tasks that require human intelligence. It has the capacity to revolutionize medicine by increasing efficiency, expediting data and image analysis and identifying patterns, trends and associations in large datasets. Within gastroenterology, recent research efforts have focused on using AI in esophagogastroduodenoscopy, wireless capsule endoscopy (WCE) and colonoscopy to assist in diagnosis, disease monitoring, lesion detection and therapeutic intervention. The main objective of this narrative review is to provide a comprehensive overview of the research being performed within gastroenterology on AI in esophagogastroduodenoscopy, WCE and colonoscopy.
Core Tip: Artificial intelligence (AI) is a complex concept that has the capacity to revolutionize medicine. Within gastroenterology, recent research efforts have focused on using AI in esophagogastroduodenoscopy, wireless capsule endoscopy (WCE) and colonoscopy to assist in diagnosis, disease monitoring, lesion detection and therapeutic intervention. This narrative review provides a comprehensive overview of the research being performed within gastroenterology on AI in esophagogastroduodenoscopy, WCE and colonoscopy.
