Morreale GC, Sinagra E, Vitello A, Shahini E, Shahini E, Maida M. Emerging artificial intelligence applications in gastroenterology: A review of the literature. Artif Intell Gastrointest Endosc 2020; 1(1): 6-18 [DOI: 10.37126/aige.v1.i1.6]
Corresponding Author of This Article
Marcello Maida, MD, Doctor, Senior Researcher, Gastroenterology and Endoscopy Unit, S. Elia–M. Raimondi Hospital, Via Giacomo Cusmano, 1, Caltanissetta 93100, Italy. marcello.maida@hotmail.it
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Minireviews
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/
Gaetano Cristian Morreale, Alessandro Vitello, Marcello Maida, Gastroenterology and Endoscopy Unit, S. Elia- M. Raimondi Hospital, Caltanissetta 93100, Italy
Emanuele Sinagra, Gastroenterology and Endoscopy Unit, Fondazione Istituto G. Giglio, Cefalù 90015, Italy
Endrit Shahini, Gastroenterology and Endoscopy Unit, Istituto di Candiolo, FPO-IRCCS, Candiolo (Torino) 93100, Italy
Erjon Shahini, Polytechnic University of Bari, Bari 70126, Italy
Author contributions: Morreale GC and Maida M are guarantors of the integrity of the entire study and contributed to the manuscript drafting and manuscript revision for important intellectual content; all authors contributed to the manuscript editing and had full control over the preparation of the manuscript.
Conflict-of-interest statement: The authors have no proprietary, financial, professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of this manuscript.
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: Marcello Maida, MD, Doctor, Senior Researcher, Gastroenterology and Endoscopy Unit, S. Elia–M. Raimondi Hospital, Via Giacomo Cusmano, 1, Caltanissetta 93100, Italy. marcello.maida@hotmail.it
Received: June 23, 2020 Peer-review started: June 23, 2020 First decision: July 3, 2020 Revised: July 7, 2020 Accepted: July 17, 2020 Article in press: July 17, 2020 Published online: July 28, 2020 Processing time: 30 Days and 3.3 Hours
Core Tip
Core tip: Artificial intelligence (AI) allows machines to provide disruptive value in a multitude of industries and knowledge domains. Applications of artificial intelligence techniques, specifically machine learning and more recently deep learning, are arising in gastrointestinal endoscopy. Computer-aided diagnosis has been performed during upper gastrointestinal endoscopy for the automated identification of dysplastic lesions in Barrett’s esophagus for preventing esophageal cancer, as well as in lower gastrointestinal endoscopy for detecting colorectal polyps to prevent colorectal cancer. The aim of this review is to investigate current data from the literature, supporting recent technologies of AI both in upper and lower gastrointestinal diseases, including Barrett's esophagus, gastric cancer, Helicobacter pylori infection, colonic polyps and colon cancer.
