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Artif Intell Gastrointest Endosc. Jul 28, 2020; 1(1): 19-27
Published online Jul 28, 2020. doi: 10.37126/aige.v1.i1.19
Techniques to integrate artificial intelligence systems with medical information in gastroenterology
Hong-Yu Jin, Man Zhang, Bing Hu
Hong-Yu Jin, Department of Liver Surgery, Liver Transplantation Center, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China
Man Zhang, Department of Gynecology and Obstetrics, West China Second University Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China
Bing Hu, Department of Gastroenterology, Endoscopy Center, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China
Author contributions: Jin HY and Hu B contributed to the conceptualization of the study; Jin HY, and Zhang M contributed to data curation, investigation, methodology, and software; Jin HY drafted the manuscript; Zhang M contributed to the formal analysis; Hu B contributed to the funding acquisition; project administration, resources and supervision; Jin HY, Zhang M, and Hu B reviewed and edited the manuscript.
Conflict-of-interest statement: None declared.
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: Bing Hu, MBBS, MD, Professor, Department of Gastroenterology, Endoscopy Center, West China Hospital, Sichuan University, No. 37, Guoxue Lane, Wuhou District, Chengdu 610041, Sichuan Province, China. hubingnj@163.com
Received: June 27, 2020
Peer-review started: June 27, 2020
First decision: July 3, 2020
Revised: July 7, 2020
Accepted: July 15, 2020
Article in press: July 15, 2020
Published online: July 28, 2020
Processing time: 25 Days and 22.1 Hours
Abstract

Gastrointestinal (GI) endoscopy is the central element in contemporary gastroenterology as it provides direct evidence to guide targeted therapy. To increase the accuracy of GI endoscopy and to reduce human-related errors, artificial intelligence (AI) has been applied in GI endoscopy, which has been proved to be effective in diagnosing and treating numerous diseases. Therefore, we review current research on the efficacy of AI-assisted GI endoscopy in order to assess its functions, advantages and how the design can be improved.

Keywords: Gastrointestinal endoscopy; Artificial intelligence; Diagnosis; Advantages

Core tip: Artificial intelligence (AI) has been the center of medical information in the 21st century and we have witnessed the tremendous change it has triggered in the diagnosis and treatment of many diseases. Gastrointestinal endoscopy is the core element of clinical procedures in modern gastroenterology as it provides direct evidence and guides precise diagnosis and treatment. Therefore, in this article, we review the latest findings on AI-assisted gastrointestinal endoscopy concerning its applications in the diagnosis and treatment of gastrointestinal diseases.