Identification of KRAS mutation in rectal cancer based on a 2.5D deep learning model
A 2.5D deep learning model can effectively distinguish between KRAS mutant and KRAS wild-type RC, outperforming traditional radiomic models. It provides a novel non-invasive approach for the preoperative assessment of KRAS mutation status.
Authors
- Guanfeng Chen
- Chengmeng Zhang (ORCID: https://orcid.org/0000-0002-9815-2293)
- Yanyan Zhou
- H. P. Peng
- Jinge Li
- Jian Shen
Institutions
- Zhejiang Chinese Medical University (CN)
- Fujian Medical University (CN)
- Huzhou Normal University (CN)
- Huzhou Central Hospital (CN)
- First Affiliated Hospital of Fujian Medical University (CN)
- County Hospital (GB)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2026-02-25
- DOI
- https://doi.org/10.3389/fonc.2026.1763859
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00