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Copyright ©The Author(s) 2018. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Endosc. Oct 16, 2018; 10(10): 239-249
Published online Oct 16, 2018. doi: 10.4253/wjge.v10.i10.239
Artificial intelligence in gastrointestinal endoscopy: The future is almost here
Muthuraman Alagappan, Jeremy R Glissen Brown, Yuichi Mori, Tyler M Berzin
Muthuraman Alagappan, Jeremy R Glissen Brown, Tyler M Berzin, Center for Advanced Endoscopy, Beth Israel Deaconess Medical Center, Harvard Medical, Boston, MA 02215, United States
Yuichi Mori, Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan
Author contributions: Alagappan M and Glissen Brown JR contributed equally to this work, and are therefore listed as co-first authors; all authors contributed to this paper with conception, literature review, drafting, editing, and approval of the final version.
Conflict-of-interest statement: Dr. Tyler Berzin is Consultant for Boston Scientific and Medtronic; and Dr. Yuichi Mori is speaking honorarium from Olympus Corp. No other 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/
Correspondence to: Tyler M Berzin, MD, Assistant Professor, Doctor, Center for Advanced Endoscopy, Division of Gastroenterology, Beth Israel Deaconess Medical Center, Harvard Medical, 330 Brookline Avenue, Boston, MA 02215, United States. tberzin@bidmc.harvard.edu
Telephone: +1-617-7548888 Fax: +1-617-6671728
Received: May 10, 2018
Peer-review started: May 10, 2018
First decision: June 6, 2018
Revised: June 9, 2018
Accepted: June 30, 2018
Article in press: June 30, 2018
Published online: October 16, 2018
Abstract

Artificial intelligence (AI) enables machines to provide unparalleled value in a myriad of industries and applications. In recent years, researchers have harnessed artificial intelligence to analyze large-volume, unstructured medical data and perform clinical tasks, such as the identification of diabetic retinopathy or the diagnosis of cutaneous malignancies. Applications of artificial intelligence techniques, specifically machine learning and more recently deep learning, are beginning to emerge in gastrointestinal endoscopy. The most promising of these efforts have been in computer-aided detection and computer-aided diagnosis of colorectal polyps, with recent systems demonstrating high sensitivity and accuracy even when compared to expert human endoscopists. AI has also been utilized to identify gastrointestinal bleeding, to detect areas of inflammation, and even to diagnose certain gastrointestinal infections. Future work in the field should concentrate on creating seamless integration of AI systems with current endoscopy platforms and electronic medical records, developing training modules to teach clinicians how to use AI tools, and determining the best means for regulation and approval of new AI technology.

Keywords: Artificial intelligence, Machine learning, Gastrointestinal endoscopy, Computer-assisted decision making, Computer-aided detection, Colonic polyps, Colonoscopy, Computer-aided diagnosis, Colorectal adenocarcinoma

Core tip: Artificial intelligence (AI) appears poised to transform several industries, including clinical medicine. Recent advances in AI technology, namely the improvement in computational power and advent of deep learning, will lead to the near-term availability of clinically relevant applications in gastrointestinal endoscopy, such as real-time, high-accuracy colon polyp detection and classification and fast, automatic processing of wireless capsule endoscopy images. Applications of AI toward gastrointestinal endoscopy will likely exponentially rise in the coming years, and attention should be paid toward regulation, approval, and effective implementation of this powerful technology.