The DOI matches its Crossref record.
Artificial Intelligence-Aided Colonoscopy Does Not Increase Adenoma Detection Rate in Routine Clinical Practice
Abstract
The performance of artificial intelligence-aided colonoscopy (AIAC) in a real-world setting has not been described. We compared adenoma and polyp detection rates (ADR/PDR) in a 6-month period before (pre-AIAC) and after introduction of AIAC (GI Genius, Medtronic) in all endoscopy suites in our large-volume center. The ADR and PDR in the AIAC group was lower compared with those in the pre-AIAC group (30.3% vs 35.2%, P < 0.001; 36.5% vs 40.9%, P = 0.004, respectively); procedure time was significantly shorter in the AIAC group. In summary, introduction of AIAC did not result in performance improvement in our large-center cohort, raising important questions on AI-human interactions in medicine.
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A few studies have reported no improvement in quality metrics for in vivo endoscopy with versus without AI assistance.
“While reviews and meta-analyses provide robust support for the widespread adoption of AI in colonoscopy, a few studies have reported no improvement in quality metrics for in vivo endoscopy with versus without AI assistance [89][90][91] .”
From Enhancing human-AI collaboration: The case of colonoscopy (2024) · cites this paper as [91]
Levy and collaborators report faster colonoscopic procedures in the CADe group.
“Consistent with this hypothesis, Levy and collaborators report faster colonoscopic procedures in the CADe group [91] .”
From Enhancing human-AI collaboration: The case of colonoscopy (2024) · cites this paper as [91]
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Research works printed but not linked: 8
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Wei, M. T., Fay, S., Yung, D., Ladabaum, U., & Kopylov, U. (2024) · Clinical and Translational Gastroenterology · doi:10.14309/ctg.0000000000000671 · Cited by 57
Self-citationEnhancing human-AI collaboration: The case of colonoscopy
Introzzi, L., Zonca, J., Cabitza, F., Cherubini, P., & Reverberi, C. (2024) · Digestive and Liver Disease · doi:10.1016/j.dld.2023.10.018 · Cited by 28
Artificial Intelligence-assisted colonoscopy and colorectal cancer screening: Where are we going?
Spadaccini, M., Troya, J., Khalaf, K., Facciorusso, A., Maselli, R., Hann, A., & Repici, A. (2024) · Digestive and Liver Disease · doi:10.1016/j.dld.2024.01.203 · Cited by 20
Metadata
- Authors
- Levy, I., Bruckmayer, L., Klang, E., Ben-Horin, S., & Kopylov, U.
- Affiliations
- Tel Aviv University (IL)
- Department of Gastroenterology, Sheba Medical Center, Ramat Gan and Tel Aviv University School of Medicine, Israel;
- Corresponding author
- Kopylov, Uri
- Venue
- American Journal of Gastroenterology
- Published
- 2022-08-23
- Volume
- 117
- Issue
- 11
- Pages
- 1871-1873
- ISSN
- 0002-9270 (ISSN-L)
- 1572-0241
- OpenAlex
- W4293277185
- Cited by
- 114
- References
- 0
- Citations by year
- 2026: 15 · 2025: 28 · 2024: 31 · 2023: 35 · 2022: 4
- FWCI
- 10.23
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The American Journal of Gastroenterology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Oncology › Colorectal Cancer Screening and Detection
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- adenoma detection rate, polyp detection rate, GI Genius, real-world performance, human-AI interaction, colorectal cancer screening
- MeSH terms
- Adenoma, Artificial Intelligence, Colonic Polyps, Colonoscopy, Humans, Colorectal Neoplasms, Adenomatous Polyps
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