The clinical validity of radiomics-based prediction of molecular subtypes in breast cancer from digital mammary tomosynthesis
The key features of BC were revealed by image omics and ML models, and a nomogram model with diagnostic value was constructed.
Authors
- Xiaocui Rong (ORCID: https://orcid.org/0000-0003-0325-296X)
- Yong Ping (ORCID: https://orcid.org/0000-0003-1066-5471)
- Taiping Qu (ORCID: https://orcid.org/0000-0001-5058-3433)
- Zhigang Li (ORCID: https://orcid.org/0000-0001-7164-1049)
- Jianhua Zhang (ORCID: https://orcid.org/0000-0001-5412-9860)
- Haoqi Wang (ORCID: https://orcid.org/0000-0002-9012-5370)
- Jingjing Tian (ORCID: https://orcid.org/0000-0003-1396-0986)
- Yilun Li (ORCID: https://orcid.org/0000-0001-7896-3374)
- Yidi Qin
- Jing Xue
- Tao Wang (ORCID: https://orcid.org/0000-0002-2597-1247)
Institutions
- Hebei Medical University (CN)
- Fourth Hospital of Hebei Medical University (CN)
- Jining Traditional Chinese Medicine Hospital (CN)
- Xingtai People's Hospital (CN)
- Hebei University of Chinese Medicine (CN)
- First Hospital of Shijiazhuang (CN)
- Cixian People's Hospital (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-10-13
- DOI
- https://doi.org/10.3389/fonc.2025.1661116
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00