Performance of Computer-Aided Detection and Quality of Bowel Preparation: A Comprehensive Analysis of Colonoscopy Outcomes
This study highlights the significant improvement in detecting diminutive polyps (< 5 mm) and sessile polyps using CADe, although notably, this benefit was only seen in patients with adequate bowel preparation. In conclusion, the integration of AI in colonoscopy, driven by artificial intelligence, promises to significantly enhance lesion detection and diagnosis, revolutionize the procedure's effectiveness, and improve patient outcomes.
Authors
- Shyam J Thakkar (ORCID: https://orcid.org/0000-0001-8671-9961)
- Douglas R. Morgan (ORCID: https://orcid.org/0000-0002-1136-0963)
- Fayez Sarkis (ORCID: https://orcid.org/0000-0003-4250-6985)
- Patricia Ajayi-Fox
- Tatiana Torres-Herman (ORCID: https://orcid.org/0000-0003-3522-4445)
- Amanda K. Cartee (ORCID: https://orcid.org/0000-0002-0197-6035)
- Dalton A. Norwood (ORCID: https://orcid.org/0000-0001-5408-560X)
- Shajan Peter (ORCID: https://orcid.org/0000-0003-3214-2989)
- Kirk Russ (ORCID: https://orcid.org/0000-0002-3088-7277)
- Ramzi Mulki (ORCID: https://orcid.org/0000-0001-5493-1407)
- Sergio A. Sánchez‐Luna (ORCID: https://orcid.org/0000-0001-6870-2226)
- Eleazar E. Montalvan-Sanchez (ORCID: https://orcid.org/0000-0002-7178-0724)
- Anam Hameed
Institutions
- West Virginia University (US)
- University of Alabama at Birmingham (US)
- Yale University (US)
Publication Details
- Journal
- Digestive Diseases and Sciences
- Published
- 2024-09-16
- DOI
- https://doi.org/10.1007/s10620-024-08610-7
- Citations
- 5
- Primary Topic
- Colorectal Cancer Screening and Detection
- Type
- article
- Field-Weighted Citation Impact
- 1.41