Strengths and weaknesses of an artificial intelligence polyp detection program as assessed by a high-detecting endoscopist
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AI performance in lesion detection has been reported as similar to the best human experts.
“Overall, AI performance in lesion detection has been reported as similar to the best human experts [41 , 42] .”
From Enhancing human-AI collaboration: The case of colonoscopy (2024) · cites this paper as [42]
The Statistical Analysis table (page unavailable) reports 671 lesions detected simultaneously by AI and a high-detecting endoscopist, supporting some similarity in detection. But the Conclusions (page unavailable) say AI missed some larger flat lesions and remained an adjunct to expert detection; the paper does not establish that its overall detection performance matches the best human experts. (LLM, conf=0.82)
Experimental — accuracy not yet measuredAvailable AI devices exhibit very high sensitivity and overall performance on par with or better than top human experts.
“Available AI devices exhibit very high sensitivity and overall performance on par with or better than top human experts [42 , 76] .”
From Enhancing human-AI collaboration: The case of colonoscopy (2024) · cites this paper as [42]
The Testing section reports that the CADe device increased adenoma detection for a high-detecting endoscopist, supporting a performance benefit. But the paper does not establish very high sensitivity or performance on par with or better than top experts across available devices: it assessed one device, reports lesions the device missed, and notes that some endoscopists without AI have exceeded detection rates achieved in AI trials. (LLM, conf=0.85)
Experimental — accuracy not yet measured
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Cites
Adenoma detection rate and risk of colorectal cancer and death
Corley, D. A., Jensen, C. D., Marks, A. R., Zhao, W. K., Lee, J. K., Doubeni, C. A., Zauber, A. G., de Boer, J., Fireman, B. H., Schottinger, J. E., et al. (2014) · New England Journal of Medicine · doi:10.1056/nejmoa1309086 · Cited by 2,270 · see citing works
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Study on detection rate of polyps and adenomas in artificial-intelligence-aided colonoscopy
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Cited by
Sorted by citations
Enhancing 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
Abduljawad, S. A. (2025) · International Journal of Computer-Assisted Language Learning and Teaching · doi:10.4018/ijcallt.367276 · Cited by 19 · see citing works
- Authors
- Rex, D. K., Mori, Y., Sharma, P., Lahr, R. E., Vemulapalli, K. C., & Hassan, C.
- Affiliations
- Indiana University School of Medicine (US)
- University of Oslo (NO)
- University of Kansas (US)
- Humanitas University (IT)
- Venue
- Gastroenterology
- Publisher
- Elsevier BV
- Published
- 2022-08
- Volume
- 163
- Issue
- 2
- Pages
- 354-358.e1
- ISSN
- 0016-5085 (ISSN-L)
- OpenAlex
- W4223516062
- Cited by
- 19
- References
- 3
- Citations by year
- 2026: 1 · 2025: 7 · 2024: 5 · 2023: 5 · 2022: 1
- FWCI
- 1.88
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Gastroenterology (publishedVersion)
- PubMed (publishedVersion)
- IUScholarWorks (Indiana University) (submittedVersion)
- Purdue University Indianapolis (Indiana University) (submittedVersion)
- Funders
- Horizon 2020 Framework Programme (101026196)
- Medtronic
- Braintree Laboratories
- Boston Scientific Corporation
- Aries Pharmaceuticals
- EndoAid
- European Commission
- Olympus
- Covidien
- 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
- artificial intelligence, polyp detection, colonoscopy, adenoma detection rate, colorectal cancer screening, operator dependence, AI performance evaluation, colorectal adenoma, interval cancer, withdrawal time, colorectal cancer prevention, endoscopy training, AI-assisted endoscopy, colorectal cancer risk stratification, colorectal cancer screening guidelines, colorectal cancer risk
- MeSH terms
- Artificial Intelligence, Colonic Polyps, Colonoscopy, Humans
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