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Artif Intell Gastrointest Endosc. Jun 28, 2021; 2(3): 79-88
Published online Jun 28, 2021. doi: 10.37126/aige.v2.i3.79
Utility of artificial intelligence in colonoscopy
Niel Shah, Abhilasha Jyala, Harish Patel, Jasbir Makker
Niel Shah, Abhilasha Jyala, Department of Internal Medicine, BronxCare Hospital Center, Bronx, NY 10457, United States
Harish Patel, Jasbir Makker, Department of Internal Medicine, Gastroenterology, BronxCare Hospital Center, Bronx, NY 10457, United States
Author contributions: Patel H conceived with an idea about this work and approved the final manuscript; Shah N, Jyala M and Makker J were responsible for reviewing of the literatures and studies, drafting the outline and main manuscript; Patel H and Makker J were responsible for critically reviewing the manuscript for intellectual content, reviewing of the literatures and editing of the main 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: Harish Patel, MD, Attending Doctor, Department of Internal Medicine, Gastroenterology, BronxCare Hospital Center, 1650 Grand Concourse , Bronx, NY 10457, United States. hpatel@bronxcare.org
Received: June 2, 2021
Peer-review started: June 2, 2021
First decision: June 18, 2021
Revised: June 20, 2021
Accepted: June 28, 2021
Article in press: June 28, 2021
Published online: June 28, 2021
Core Tip

Core Tip: Artificial intelligence (AI) pertains to performance of intelligent tasks like human beings by computer-controlled machines. Machine learning, one of the most important and fundamental principles of AI, essentially means automatically using the available data to learn and make decisions without human intervention. AI based detection models have been developed for polyp detection and to differentiate malignant from nonmalignant lesions. It has been also utilized to analyze endoscopic images for inflammatory bowel disease diagnosis, grading its severity and predicting treatment response.