Comparative analysis of deep learning and radiomics models in predicting hepatocellular carcinoma differentiation via ultrasound
Integrating radiomics and deep learning enhances the predictive accuracy of ultrasound-based models for HCC differentiation, providing a promising non-invasive approach for preoperative evaluation.
Authors
- Junlei Qian (ORCID: https://orcid.org/0000-0003-4952-9880)
- Hongwei Qian (ORCID: https://orcid.org/0000-0002-6724-9826)
- Baochun Lu
- Luohang Xu
- Hong Fu
- Yanhua Huang (ORCID: https://orcid.org/0000-0002-5732-0203)
- Jianhua Yu (ORCID: https://orcid.org/0000-0002-6661-6647)
- Yalan Zheng
Institutions
- Shaoxing University (CN)
- Shaoxing People's Hospital (CN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-09-26
- DOI
- https://doi.org/10.3389/fmed.2025.1685725
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36