Macrotrabecular-massive subtype in hepatocellular carcinoma based on contrast-enhanced CT: deep learning outperforms machine learning
The RVCL model can accurately predict the MTM subtype. Deep learning outperforms machine learning for predicting MTM subtype. RVCL boosts accuracy and guides personalized therapy.
Authors
- Jinkui Li
- Jianxin Zhao (ORCID: https://orcid.org/0000-0002-0198-676X)
- Gang Huang (ORCID: https://orcid.org/0000-0003-0012-4161)
- Zeyan Li (ORCID: https://orcid.org/0000-0002-3529-5879)
- Hao Xu (ORCID: https://orcid.org/0000-0002-6979-3761)
- Lulu Jia (ORCID: https://orcid.org/0000-0003-1616-896X)
- H. J. Jiang (ORCID: https://orcid.org/0009-0000-7962-6732)
- Junqiang Lei (ORCID: https://orcid.org/0000-0002-7632-1922)
Institutions
- Brigham and Women's Hospital (US)
- Harvard University (US)
- University of California, Los Angeles (US)
- University of Jinan (CN)
- Gansu Provincial Hospital (CN)
- First Hospital of Lanzhou University (CN)
- Lanzhou University (CN)
Publication Details
- Journal
- Insights into Imaging
- Published
- 2025-08-28
- DOI
- https://doi.org/10.1186/s13244-025-02063-w
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36
Funders
- Lanzhou Science and Technology Bureau