©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
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, 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.
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
Processing time: 160 Days and 0.5 Hours
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
Processing time: 160 Days and 0.5 Hours
Core Tip
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.