An interpretable contrast-enhanced CT radiomics–based pipeline incorporating automatic segmentation for predicting ISUP grade group in ccRCC
The interpretable pipeline may have potential as a non-invasive tool for predicting ISUP GG in ccRCC.
Authors
- Fei Yang (ORCID: https://orcid.org/0000-0002-5513-5725)
- Wanjun Zheng
- Yue Ren (ORCID: https://orcid.org/0000-0002-1975-8896)
- Yuanping Tao
- He Chao
- Feng Cui (ORCID: https://orcid.org/0000-0002-5186-5720)
- Shuchao Kang
- Min Xu (ORCID: https://orcid.org/0000-0002-3761-1396)
- Yongsheng Zhang (ORCID: https://orcid.org/0009-0009-0714-3374)
Institutions
- Zhejiang Chinese Medical University (CN)
- Affiliated Hangzhou First People's Hospital, Westlake University, School of Medicine (CN)
- First Affiliated Hospital Zhejiang University (CN)
- Zhejiang University of Finance and Economics (CN)
Publication Details
- Journal
- BMC Medical Imaging
- Published
- 2025-10-31
- DOI
- https://doi.org/10.1186/s12880-025-01984-8
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00