Jin HY, Zhang M, Hu B. Techniques to integrate artificial intelligence systems with medical information in gastroenterology. Artif Intell Gastrointest Endosc 2020; 1(1): 19-27 [DOI: 10.37126/aige.v1.i1.19]
Corresponding Author of This Article
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
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Minireviews
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/
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.
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.
