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Study on detection rate of polyps and adenomas in artificial-intelligence-aided colonoscopy
Open accessAbstract
BACKGROUND/AIM: To study the impact of computer-aided detection (CADe) system on the detection rate of polyps and adenomas in colonoscopy. MATERIALS AND METHODS: A total of 1026 patients were prospectively randomly scheduled for colonoscopy with (the CADe group, CADe) or without (the control group, CON) the aid of the CADe system, together with visual notification and voice alarm, so as to compare the detection rate of polyp. RESULTS: Compared with group CON, the detection rate of adenomas increased in group CADe, the average number of adenomas increased, the number of small adenomas increased, the number of proliferative polyps increased, and the differences were statistically significant (P < 0.001), but the comparison for the number of larger adenomas showed no significant difference between the groups (P> 0.05). CONCLUSIONS: The CADe system is feasible for increasing the detection of polyps and adenomas in colonoscopy.
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“The study revealed that the CADe group had a 5.8% increase in adenoma detection compared to the standard group.”
From Advancing Colorectal Cancer Screening: A Comprehensive Systematic Review of Artificial Intelligence (AI)-Assisted Versus Routine Colonoscopy (2023) · cites this paper as [15]
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“This method also enhanced the detection of small adenomas and proliferative polyps with a statistically significant difference (p<0.001).”
From Advancing Colorectal Cancer Screening: A Comprehensive Systematic Review of Artificial Intelligence (AI)-Assisted Versus Routine Colonoscopy (2023) · cites this paper as [15]
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Metadata
- Authors
- Huang, J., Liu, W.-N., Zhang, Y.-Y., Bian, X.-Q., Wang, L.-J., Yang, Q., & Zhang, X.-D.
- Affiliations
- The 988th Hospital of the Joint Service Support Force of the Chinese People's Liberation Army (CN)
- Corresponding author
- Huang, Jin
- ORCID
- Huang, Jin
- Venue
- Saudi Journal of Gastroenterology
- Published
- 2020
- Volume
- 26
- Issue
- 1
- Pages
- 13
- ISSN
- 1319-3767 (ISSN-L)
- PMC
- PMC7045775
- OpenAlex
- W2997497159
- Cited by
- 179
- References
- 28
- Citations by year
- 2026: 14 · 2025: 22 · 2024: 20 · 2023: 32 · 2022: 29 · 2021: 39 · 2020: 23
- FWCI
- 9.51
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by-nc-sa
- Locations
- Saudi Journal of Gastroenterology (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion, cc-by-nc-sa)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- 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, colonoscopy, colorectal polyps, colorectal adenoma, polyp detection rate, small adenomas, voice alarm
- MeSH terms
- Adenoma, Adult, Artificial Intelligence, Colonic Polyps, Colonoscopy, Diagnosis, Computer-Assisted, Female, Humans, Male, Middle Aged, Prospective Studies
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