AI in colonoscopy-detection and characterisation of malignant polyps

Advanced search
Browse by:

Department | Year

UCL Theses | Latest

Deposit your research

AI in colonoscopy-detection and characterisation of malignant polyps

Shakir, T; Kader, R; Bhan, C; Chand, M; (2023) AI in colonoscopy-detection and characterisation of malignant polyps. Artificial Intelligence Surgery , 3 pp. 186-194. 10.20517/ais.2023.17. Green open access

Preview

Text
ais3017.pdf - Published Version
Download (316kB) | Preview

Abstract

The medical technological revolution has transformed the nature with which we deliver care. Adjuncts such as artificial intelligence and machine learning have underpinned this. The applications to the field of endoscopy are numerous. Malignant polyps represent a significant diagnostic dilemma as they lie in an area in which mischaracterisation may mean the difference between an endoscopic procedure and a formal bowel resection. This has implications for patients’ oncological outcomes, morbidity and mortality, especially if post-procedure histopathology upstages disease. We have made significant strides with the applications of artificial intelligence to colonoscopic detection. Deep learning algorithms are able to be created from video and image databases. These have been applied to traditional, human-derived, classification methods, such as Paris or Kudo, with up to 93% accuracy. Furthermore, multimodal characterisation systems have been developed, which also factor in patient demographics and colonic location to provide an estimation of invasion and endoscopic resectability with over 90% accuracy. Although the technology is still evolving, and the lack of high-quality randomised controlled trials limits clinical usability, there is an exciting horizon upon us for artificial intelligence-augmented endoscopy.

Type:	Article
Title:	AI in colonoscopy-detection and characterisation of malignant polyps
Open access status:	An open access version is available from UCL Discovery
DOI:	10.20517/ais.2023.17
Publisher version:	https://doi.org/10.20517/ais.2023.17
Language:	English
Additional information:	© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Keywords:	Colonoscopy, artificial intelligence, malignant polyps
UCL classification:	UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci > Department of Targeted Intervention
URI:	https://discovery.ucl.ac.uk/id/eprint/10184311