Sinagra E, Badalamenti M, Maida M, Spadaccini M, Maselli R, Rossi F, Conoscenti G, Raimondo D, Pallio S, Repici A, Anderloni A. Use of artificial intelligence in improving adenoma detection rate during colonoscopy: Might both endoscopists and pathologists be further helped. World J Gastroenterol 2020; 26(39): 5911-5918 [PMID: 33132644 DOI: 10.3748/wjg.v26.i39.5911]
Corresponding Author of This Article
Emanuele Sinagra, MD, PhD, Senior Researcher, Gastroenterology and Endoscopy Unit, Fondazione Istituto San Raffaele Giglio, Contrada Pietra Pollastra Pisciotto, Cefalù 90015, Italy. emanuelesinagra83@googlemail.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Opinion 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/
World J Gastroenterol. Oct 21, 2020; 26(39): 5911-5918 Published online Oct 21, 2020. doi: 10.3748/wjg.v26.i39.5911
Use of artificial intelligence in improving adenoma detection rate during colonoscopy: Might both endoscopists and pathologists be further helped
Emanuele Sinagra, Matteo Badalamenti, Marcello Maida, Marco Spadaccini, Roberta Maselli, Francesca Rossi, Giuseppe Conoscenti, Dario Raimondo, Socrate Pallio, Alessandro Repici, Andrea Anderloni
Emanuele Sinagra, Francesca Rossi, Giuseppe Conoscenti, Dario Raimondo, Gastroenterology and Endoscopy Unit, Fondazione Istituto San Raffaele Giglio, Cefalù 90015, Italy
Matteo Badalamenti, Marco Spadaccini, Roberta Maselli, Alessandro Repici, Andrea Anderloni, Digestive Endoscopy Unit, Division of Gastroenterology, Humanitas Clinical and Research Center IRCCS, Rozzano 20089, Italy
Marcello Maida, Gastroenterology and Endoscopy Unit, S. Elia-Raimondi Hospital, Caltanissetta 93100, Italy
Socrate Pallio, Endoscopy Unit, AOUP Policlinico G. Martino, Messina 98125, Italy
Author contributions: Sinagra E designed the study; Sinagra E, Badalamenti M, Maida M, Spadaccini M, Maselli R, Rossi F and Conoscenti G wrote the paper; Pallio S, Raimondo D, Anderloni A and Repici A supervised the work.
Conflict-of-interest statement: Authors declare no conflict of interests for this article.
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: Emanuele Sinagra, MD, PhD, Senior Researcher, Gastroenterology and Endoscopy Unit, Fondazione Istituto San Raffaele Giglio, Contrada Pietra Pollastra Pisciotto, Cefalù 90015, Italy. emanuelesinagra83@googlemail.com
Received: July 27, 2020 Peer-review started: July 27, 2020 First decision: August 8, 2020 Revised: August 18, 2020 Accepted: September 23, 2020 Article in press: September 23, 2020 Published online: October 21, 2020 Processing time: 86 Days and 1 Hours
Core Tip
Core Tip: Artificial intelligence is an emerging technology which application is rapidly increasingin numerous medical fields. The several applications of artificial intelligence in gastroenterology are showing promising results, especially in the setting of gastrointestinal oncology. Among these, the techniques able to increase the Adenoma detection rate will play a key role in reducing the colorectal cancer incidence and its related mortality caused by undetected or missclassified interval cancers. Furthermore, a significant reduction in costs is also expected. In addition the assistance of the Computer-aided detection and diagnosis systems will lead to a reduction of the examination time and therefore an optimization of the endoscopic schedule.
