A dual-modality machine learning precision diagnostic model integrated radiomics and proteomics for breast cancer
This study confirmed for the synergistic diagnostic value of plasma proteins and ultrasound images, providing a new strategy with both accuracy and accessibility for stratified diagnosis of breast cancer.
Authors
- J. S. Lu
- Pengping Li (ORCID: https://orcid.org/0009-0005-5984-8297)
- Shuirong Zhang (ORCID: https://orcid.org/0000-0002-0950-8738)
- Junli Gao (ORCID: https://orcid.org/0000-0002-0327-3616)
- Lanqing Li (ORCID: https://orcid.org/0000-0003-1998-4022)
- Yuqin Huang (ORCID: https://orcid.org/0000-0003-0608-827X)
- Zhenyu Wang (ORCID: https://orcid.org/0000-0002-5114-435X)
- Jiayi Liu (ORCID: https://orcid.org/0009-0008-0848-1650)
- Yuan Liu (ORCID: https://orcid.org/0000-0002-1361-0882)
- Kexin Yin
- Liu Ren
- Ke Sun (ORCID: https://orcid.org/0000-0002-6742-3484)
- Claire Y. Tong
Institutions
- Zhejiang Chinese Medical University (CN)
- Phillips Academy (US)
- The First People's Hospital of Xiaoshan District, Hangzhou (CN)
- Salisbury University (US)
Publication Details
- Journal
- Frontiers in Immunology
- Published
- 2025-11-06
- DOI
- https://doi.org/10.3389/fimmu.2025.1665459
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36