Artificial intelligence technologies for the detection of colorectal lesions: The future is now Article

Full Text via DOI: 10.3748/wjg.v26.i37.5606 Web of Science: 000582755000005
International Collaboration

Cited authors

  • Attardo S, Chandrasekar VT, Spadaccini M, Maselli R, Patel HK, Desai M, Capogreco A, Badalamenti M, Galtieri PA, Pellegatta G, Fugazza A, Carrara S, Anderloni A, Occhipinti P, Hassan C, Sharma P, Repici A

Abstract

  • Several studies have shown a significant adenoma miss rate up to 35% during screening colonoscopy, especially in patients with diminutive adenomas. The use of artificial intelligence (AI) in colonoscopy has been gaining popularity by helping endoscopists in polyp detection, with the aim to increase their adenoma detection rate (ADR) and polyp detection rate (PDR) in order to reduce the incidence of interval cancers. The efficacy of deep convolutional neural network (DCNN)-based AI system for polyp detection has been trained and tested inex vivosettings such as colonoscopy still images or videos. Recent trials have evaluated the real-time efficacy of DCNN-based systems showing promising results in term of improved ADR and PDR. In this review we reported data from the preliminaryex vivoexperiences and summarized the results of the initial randomized controlled trials.

Publication date

  • 2020

Published in

International Standard Serial Number (ISSN)

  • 1007-9327

Number of pages

  • 11

Start page

  • 5606

End page

  • 5616

Volume

  • 26

Issue

  • 37