Computer-aided detection of polyps does not improve colonoscopist performance in a pragmatic implementation trial
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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 [90]
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Making sense of implementation theories, models and frameworks
Nilsen, P. (2015) · Implementation Science · doi:10.1186/s13012-015-0242-0 · Cited by 4,447 · see citing works
Designing Difference in Difference Studies: Best Practices for Public Health Policy Research
Wing, C., Simon, K., & Bello-Gomez, R. A. (2018) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-040617-013507 · Cited by 1,470 · see citing works
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Research works printed but not linked: 10
- [1]Schottinger JE, JAMA 2022; 327: 2114– 2122. 35670788 PMC9175074
- [2]Repici A, Gastroenterology 2020; 159: 512– 520. 32371116
- [3]Repici A, Gut 2022; 71: 757– 765. 34187845
- [4]Wallace MB, Gastroenterology 2022; 163: 295– 304. 35304117
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- [10]Nilsen P Implement Sci 2015; 10: 53. 25895742 PMC4406164
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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 · see citing works
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 · see citing works
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 · see citing works
- Authors
- Ladabaum, U., Shepard, J., Weng, Y., Desai, M., Singer, S. J., & Mannalithara, A.
- Affiliations
- Stanford Medicine (US)
- Stanford Health Care (US)
- Corresponding author
- Ladabaum, Uri
- Venue
- Gastroenterology
- Publisher
- Elsevier BV
- Published
- 2023-03
- Volume
- 164
- Issue
- 3
- Pages
- 481-483.e6
- ISSN
- 0016-5085 (ISSN-L)
- PMC
- PMC11521095
- OpenAlex
- W4311455841
- Cited by
- 100
- References
- 2
- Citations by year
- 2026: 18 · 2025: 18 · 2024: 31 · 2023: 33
- FWCI
- 8.50
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Gastroenterology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (UL1TR003142)
- National Center for Advancing Translational Sciences
- Topics
- Health Sciences › Medicine › Oncology › Colorectal Cancer Screening and Detection
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Health Sciences › Medicine › Oncology › Colorectal Cancer Surgical Treatments
- Keywords
- computer-aided detection, colorectal polyps, colonoscopy, adenoma detection rate, artificial intelligence in endoscopy, polyp characterization, implementation trial
- MeSH terms
- Colonic Polyps, Colonoscopy, Computers, Humans, Radiographic Image Interpretation, Computer-Assisted, Sensitivity and Specificity, Colonography, Computed Tomographic
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