Artificial Intelligence for Colonoscopy- Beyond Polyp Detection – A Review of where we are Today and where AI can Take us

Angela Hsu
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Angela Hsu: University of Irvine, California Gastroenterology Department, USA

Biomedical Journal of Scientific & Technical Research, 2023, vol. 49, issue 3, 40736-40739

Abstract: Colorectal cancer (CRC) is the second leading cause of cancer-related death worldwide [1]. Colonoscopy with polypectomy is the most effective way to prevent CRC. The best outcome requires a detection rate that approaches the true prevalence of precancerous polyps. Unfortunately, detection rates vary widely among colonoscopists, prompting the development of new technologies and techniques to improve polyp detection. Toward this aim, Artificial Intelligence (AI) for screening and surveillance colonoscopy has emerged, including computer-assisted polyp detection (CADe) and characterization (CADx). On the heels of CADe and CADx are upcoming computer-aided algorithms designed to track colonoscopy quality metrics, which we coin “CAQ.†Examples of CAQ metrics include automated detection of bowel prep score and cecal intubation/withdrawal time, all of which correlate with improved detection. In this review, we describe how the incorporation of CADe, CADx, and CAQ may optimize the colonoscopy outcomes for both patients and physicians.

Keywords: Journals on Medical Drug and Therapeutics; Journals on Emergency Medicine; Physical Medicine and Rehabilitation; Journals on Infectious Diseases Addiction Science and Clinical Pathology; Open Access Clinical and Medical Journal; Journals on Biomedical Science; List of Open Access Medical Journal; Journals on Biomedical Engineering; Open Access Medical Journal; Biomedical Science Articles; Journal of Scientific and Technical Research (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:abf:journl:v:49:y:2023:i:3:p:40736-40739

DOI: 10.26717/BJSTR.2023.49.007812

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