Editorial
Copyright ©The Author(s) 2019. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Meta-Anal. Jul 31, 2019; 7(7): 343-345
Published online Jul 31, 2019. doi: 10.13105/wjma.v7.i7.343
Artificial intelligence for endoscopy
Hiroyuki Imaeda, Yoshikazu Tsuzuki, Kazuya Miyaguchi, Keigo Ashitani, Hideki Ohgo, Hidetomo Nakamoto
Hiroyuki Imaeda, Yoshikazu Tsuzuki, Hideki Ohgo, Department of Gastroenterology, Saitama Medical University, Iruma-gun, Saitama 3500495, Japan
Kazuya Miyaguchi, Keigo Ashitani, Hidetomo Nakamoto, Department of General Internal Medicine, Saitama Medical University, Iruma-gun, Saitama 3500495, Japan
Author contributions: Imaeda H made the conception, designed the study and drafted of the article; Miyaguchi K, Ashitani K, Tsuzuki Y, Nakamoto H critical revised the article for important intellectual content; Imaeda H, Tsuzuki Y, Miyaguchi K, Ashitani K, Nakamoto H made the final approval of the article.
Conflict-of-interest statement: The authors have no conflict of interest to declare.
Open-Access: 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/
Corresponding author: Hiroyuki Imaeda, MD, Professor, Department of Gastroenterology, Saitama Medical University, Morohongo 38, Moroyama-machi, Iruma-gun, Saitama 3500495, Japan. imaedahi@yahoo.co.jp
Telephone: +81-49-2761667 Fax: +81-49-2761667
Received: June 25, 2019
Peer-review started: June 25, 2019
First decision: July 20, 2019
Revised: July 27, 2019
Accepted: July 29, 2019
Article in press: July 29, 2019
Published online: July 31, 2019
Processing time: 36 Days and 16.2 Hours
Abstract

In recent times, there has been progressive development in artificial intelligence (AI) following the introduction of deep learning in the medical field including gastroenterology and endoscopy. Most of the reported studies were based on retrospective data. Several prospective studies of real-time diagnosis of moving images using the AI system are expected to match the real clinical situation and to aid the endoscopists in the detection and diagnosis of neoplasms without missing any lesion. AI can read a large number of endoscopic images in a few minutes and make a diagnosis; therefore, it is expected to cover the lack of support for the screening esophagogastroduodenoscopy in the health check-up and a large number of capsule images, thereby freeing the endoscopists from this burden. AI can help make the diagnosis during the endoscopic procedure and thereby prevent an unnecessary biopsy for patients taking antithrombotic drugs. AI can also be useful for education and training in endoscopy. Trainees can learn to perform endoscopy and the detection and diagnosis of lesions by the support of AI. In the near future, real-time endoscopic diagnosis using AI is expected to lessen the burden of endoscopists, to enhance the quality level of endoscopists, to overcome the miss of lesions and to make optimal diagnosis.

Keywords: Artificial Intelligence; Endoscopy; Gastric cancer; Colonic neoplasm

Core tip: Artificial intelligence (AI) has an increasing role in medical imaging in recent times. It has numerous benefits in the field of endoscopy. It aids in the accurate identification and diagnosis of lesions. AI also helps in reading and accurately interpreting large volumes of endoscopic images. It can play a role in the training of endoscopists as well.