Tee CHN, Ravi R, Ang TL, Li JW. Role of artificial intelligence in Barrett’s esophagus. Artif Intell Gastroenterol 2023; 4(2): 28-35 [DOI: 10.35712/aig.v4.i2.28]
Corresponding Author of This Article
James Weiquan Li, FRCPE, MBBS, MMed, Assistant Professor, Doctor, Department of Gastroenterology and Hepatology, Changi General Hospital, Singapore Health Services, 2 Simei Street 3, Singapore 529889, Singapore. james.li.w.q@singhealth.com.sg
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/
Role of artificial intelligence in Barrett’s esophagus
Chin Hock Nicholas Tee, Rajesh Ravi, Tiing Leong Ang, James Weiquan Li
Chin Hock Nicholas Tee, Rajesh Ravi, Tiing Leong Ang, James Weiquan Li, Department of Gastroenterology and Hepatology, Changi General Hospital, Singapore Health Services, Singapore 529889, Singapore
Author contributions: Tee NCH performed the literature search and drafted the manuscript; Ravi R performed the literature search and drafted the manuscript; Ang TL was involved in the drafting of the manuscript; Li JW conceptualized the title of the project, performed the literature search and was involved in the drafting of the manuscript; all authors vetted and approved the final manuscript.
Conflict-of-interest statement: There is no conflict of interest associated with any of the authors who contributed their efforts in this manuscript.
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: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: James Weiquan Li, FRCPE, MBBS, MMed, Assistant Professor, Doctor, Department of Gastroenterology and Hepatology, Changi General Hospital, Singapore Health Services, 2 Simei Street 3, Singapore 529889, Singapore. james.li.w.q@singhealth.com.sg
Received: March 6, 2023 Peer-review started: March 6, 2023 First decision: May 9, 2023 Revised: May 17, 2023 Accepted: June 12, 2023 Article in press: June 12, 2023 Published online: September 8, 2023 Processing time: 184 Days and 22.5 Hours
Abstract
The application of artificial intelligence (AI) in gastrointestinal endoscopy has gained significant traction over the last decade. One of the more recent applications of AI in this field includes the detection of dysplasia and cancer in Barrett’s esophagus (BE). AI using deep learning methods has shown promise as an adjunct to the endoscopist in detecting dysplasia and cancer. Apart from visual detection and diagnosis, AI may also aid in reducing the considerable interobserver variability in identifying and distinguishing dysplasia on whole slide images from digitized BE histology slides. This review aims to provide a comprehensive summary of the key studies thus far as well as providing an insight into the future role of AI in Barrett’s esophagus.
Core Tip: Barrett’s esophagus is a significant precursor to esophageal adenocarcinoma. Detection of dysplasia or neoplastic changes in Barrett’s esophagus can often be difficult as endoscopic changes can be subtle. Artificial intelligence has the potential to aid endoscopist in detecting such lesions endoscopically and also reduce the inter-observer variability in detecting dysplasia in Barrett’s esophagus histologically.
