Deep learning model for detecting high-grade dysplasia in colorectal adenomas
This study demonstrates that deep learning models can accurately distinguish between colonic adenomas with LGD and HGD. Training on a larger dataset could increase the accuracy and generalizability of the model and should be a focus of further studies.
Authors
- Ashistaru Saha (ORCID: https://orcid.org/0009-0001-3091-1433)
- Raavi Gupta (ORCID: https://orcid.org/0000-0003-4647-0553)
- Rong Xia (ORCID: https://orcid.org/0000-0001-8573-2152)
- Eric Steimetz (ORCID: https://orcid.org/0000-0002-4990-7506)
- Zeliha Celen Simsek
Institutions
- SUNY Downstate Health Sciences University (US)
- New York University (US)
Publication Details
- Journal
- Journal of Pathology Informatics
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1016/j.jpi.2025.100441
- Citations
- 1
- Primary Topic
- Colorectal Cancer Screening and Detection
- Type
- article
- Field-Weighted Citation Impact
- 1.05