Predicting the efficacy of neoadjuvant chemotherapy in breast cancer patients based on ultrasound longitudinal temporal depth network fusion model
The Integrated model, which incorporated pre-NAC treatment and early treatment ultrasound data and clinical features, accurately predicted pCR after NAC in breast cancer patients and provided valuable insights for personalized treatment strategies, allowing for timely adjustment of chemotherapy regimens.
Authors
- Fei‐Fei Liu (ORCID: https://orcid.org/0000-0003-4344-6486)
- Yuyuan Xu (ORCID: https://orcid.org/0000-0002-7109-1283)
- Jie Yang (ORCID: https://orcid.org/0000-0001-5839-7993)
- Wenjuan Wang (ORCID: https://orcid.org/0000-0003-1873-8364)
- Xiaodan Feng
- Yao Du
- Yan Shi (ORCID: https://orcid.org/0000-0003-1671-860X)
- Meng Wu (ORCID: https://orcid.org/0000-0003-2111-2645)
- Guanghe Cui
Institutions
- Binzhou Medical University (CN)
- Shandong University of Aeronautics (CN)
- Shandong University (CN)
- Weihai Municipal Hospital (CN)
Publication Details
- Journal
- Breast Cancer Research
- Published
- 2025-02-27
- DOI
- https://doi.org/10.1186/s13058-025-01971-5
- Citations
- 9
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 12.24
Funders
- Natural Science Foundation of Shandong Province
- Binzhou Medical University