St. Gallen International Breast Cancer Consensus-Based Clinical Decision Validation: Concordance Assessment Between Deep Large Language Model Outputs and Global Expert Panel Recommendations
DeepSeek models showed moderate concordance in following the consensus of breast cancer expert panel and showed significant advantages in answer robustness, suggesting that DeepSeek has great application potential in the field of clinical decision-making for breast cancer.
Authors
- Zhao Sun (ORCID: https://orcid.org/0000-0002-2540-9406)
- Wei Zhang
- Chenrong Zhang
- Zhihao Liu
- Yu Ren
- Bin Wang
- Chenglong Duan
- Lizhe Zhu
- Jianing Zhang
- Yi Pan
- Keyuan Du
- Jinsui Du
Institutions
- Zhengzhou University (CN)
- First Affiliated Hospital of Xi'an Jiaotong University (CN)
- Xi'an Jiaotong University (CN)
Publication Details
- Journal
- Annals of Surgical Oncology
- Published
- 2026-02-10
- DOI
- https://doi.org/10.1245/s10434-026-19176-1
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 31.92
Funders
- National Natural Science Foundation of China
- Yakult Bio-Science Foundation
- Key Research and Development Projects of Shaanxi Province