A deep learning radiomics model for predicting non-sentinel lymph node metastases in early-stage breast cancer patients
The CAR model had the capability to predict NSLN metastases in early-stage breast cancer with 1-2 positive SLN metastases.
Authors
- J F Li (ORCID: https://orcid.org/0000-0003-4270-0681)
- Yuxin Miao (ORCID: https://orcid.org/0000-0001-8419-6511)
- Angelos Stefanidis (ORCID: https://orcid.org/0000-0002-4703-8765)
- Jieying Chen (ORCID: https://orcid.org/0000-0001-8042-947X)
- Taoyu Wu (ORCID: https://orcid.org/0009-0008-7991-6869)
- Mian Zhou (ORCID: https://orcid.org/0000-0003-2514-4433)
- Jionglong Su (ORCID: https://orcid.org/0000-0001-5360-6493)
- Zongbing You (ORCID: https://orcid.org/0000-0001-5048-2229)
- Kai Zhang (ORCID: https://orcid.org/0000-0002-6550-976X)
Institutions
- Tongji University (CN)
- Shanghai Medical College of Fudan University (CN)
- University of Liverpool (GB)
- Fudan University (CN)
- Fudan University Shanghai Cancer Center (CN)
- Shanghai Tenth People's Hospital (CN)
- Xi’an Jiaotong-Liverpool University (CN)
Publication Details
- Journal
- Future Oncology
- Published
- 2025-11-30
- DOI
- https://doi.org/10.1080/14796694.2025.2595688
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00