Editorial
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
Artif Intell Gastroenterol. Aug 8, 2024; 5(2): 91336
Published online Aug 8, 2024. doi: 10.35712/aig.v5.i2.91336
Will artificial intelligence reach any limit in gastroenterology?
Joseph Bou Jaoude, Rose Al Bacha, Bassam Abboud
Joseph Bou Jaoude, Rose Al Bacha, Department of Gastroenterology, Levant Hospital, Beirut 166830, Lebanon
Bassam Abboud, Department of General Surgery, Geitaoui Hospital, Faculty of Medicine, Lebanese University, Lebanon, Beirut 166830, Lebanon
Author contributions: Abboud B designed the research; Bou Jaoude J and Al Bacha R performed the research; Bou Jaoude J, Al Bacha R and Abboud B analyzed the data; Bou Japude J, Al Bacha R and Abboud B wrote the paper.
Conflict-of-interest statement: The authors declare no conflicts 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: Bassam Abboud, MD, Professor, Department of General Surgery, Geitaoui Hospital, Faculty of Medicine, Lebanese University, Lebanon, Rmeil, Beirut 166830, Lebanon. dbabboud@yahoo.fr
Received: December 27, 2023
Revised: April 25, 2024
Accepted: June 7, 2024
Published online: August 8, 2024
Processing time: 225 Days and 1.4 Hours
Core Tip

Core Tip: The field of gastrointestinal endoscopy is an essential tool in the management of digestive diseases. Despite ongoing advancements in endoscopic technology, the incidence of missed pre-neoplastic and neoplastic lesions remains high. This is attributed to the operator-dependent nature of endoscopy, resulting in variability in detection rates and the characterization of lesions among endoscopists. To enhance endoscopic performance, it is imperative to minimize the "cognitive errors" made by the endoscopist. Artificial Intelligence, being operator-independent, could potentially serve as an unlimited solution.