Personalized prediction of breast cancer candidates for Anti-HER2 therapy using 18F-FDG PET/CT parameters and machine learning: a dual-center study
ML models that incorporate <sup>18</sup>F-FDG PET/CT parameters and clinicopathological features can aid in the prediction of different HER2 expression statuses in breast cancer.
Authors
- Yuetao Wang (ORCID: https://orcid.org/0000-0003-2859-8625)
- Zhenguo Sun (ORCID: https://orcid.org/0000-0002-3485-4034)
- Wenji Yu
- Jianxiong Gao
- Peng Chen (ORCID: https://orcid.org/0000-0002-8210-8562)
- Xiaoshuai Yuan (ORCID: https://orcid.org/0000-0002-4036-0575)
- Peng Du
Institutions
- Soochow University (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-05-14
- DOI
- https://doi.org/10.3389/fonc.2025.1590769
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Government of Jiangsu Province
- Soochow University