Current status and limitations of artificial intelligence in colonoscopy. Issue 5 (7th June 2021)

• Record Type: Journal Article
• Authors: Hann, Alexander; Troya, Joel; Fitting, Daniel
• Is Part Of: United European Gastroenterology journal. Volume 9:Issue 5(2021)
• Page Start: 527
• Page End: 533
• Publication Date: 2021-06-07
• Subjects: colonic polyps -- colonoscopy -- colorectal neoplasms -- computer‐assisted -- deep learning -- diagnosis -- endoscopy -- gastrointestinal; Gastroenterology -- Periodicals; Periodicals; 616.33005
• DOI: 10.1002/ueg2.12108
• Languages: English
• ISSNs: 2050-6406

Abstract

Abstract: Background: Artificial intelligence (AI) using deep learning methods for polyp detection (CADe) and characterization (CADx) is on the verge of clinical application. CADe already implied its potential use in randomized controlled trials. Further efforts are needed to take CADx to the next level of development. Aim: This work aims to give an overview of the current status of AI in colonoscopy, without going into too much technical detail. Methods: A literature search to identify important studies exploring the use of AI in colonoscopy was performed. Results: This review focuses on AI performance in screening colonoscopy summarizing the first prospective trials for CADe, the state of research in CADx as well as current limitations of those systems and legal issues.