Application of an Automated Deep Learning Program to A Diagnostic Classification Model: Differentiating High‐Risk Adenomas Among Colorectal Polyps 10 mm or Smaller
The CADx model established by the automated DL program showed high diagnostic performance in differentiating high- and low-risk adenomas among colorectal polyps ≤ 10 mm. The performance of the model was comparable to the experts and superior to the trainees.
Authors
- Jae Gon Lee (ORCID: https://orcid.org/0000-0003-2930-8159)
- Sung‐Jin Hong (ORCID: https://orcid.org/0000-0003-4893-039X)
- Sea Hyub Kae
- Hyun Joo Jang (ORCID: https://orcid.org/0000-0003-4424-1968)
- Chang Kyo Oh (ORCID: https://orcid.org/0000-0002-3401-1133)
- Da Ye Ham
Institutions
- Hallym University Kangnam Sacred Heart Hospital (KR)
- Hanyang University Guri Hospital (KR)
- Hallym University Dongtan Sacred Heart Hospital (KR)
Publication Details
- Journal
- Journal of Digestive Diseases
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1111/1751-2980.13340
- Citations
- 1
- Primary Topic
- Colorectal Cancer Screening and Detection
- Type
- article
- Field-Weighted Citation Impact
- 1.05
Funders
- National Research Foundation
- National Research Foundation of Korea
- Ministry of Science and ICT, South Korea