CT-based deep learning for preoperative prediction of pathological grading of renal clear cell carcinoma
The SE-ResNet34 model based on parenchymal phase CT images has excellent ability to differentiate WHO/ISUP grades of ccRCC, providing an effective noninvasive auxiliary tool for preoperative pathological grading prediction in clinical practice. However, the model's robustness and multi-center applicability need further validation before clinical use."
Authors
- Wenzeng Yang
- Tao Ma (ORCID: https://orcid.org/0000-0002-7094-6868)
- Kun Liu (ORCID: https://orcid.org/0000-0001-7608-1335)
- Bingye Shi
- Zhenyu Cui (ORCID: https://orcid.org/0000-0002-7548-3866)
Institutions
- Affiliated Hospital of Hebei University (CN)
- Hebei University (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-10-17
- DOI
- https://doi.org/10.3389/fonc.2025.1656244
- Primary Topic
- Renal cell carcinoma treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Hebei University