Predicting PIK3CA mutation in breast cancer with machine learning based multimodal image radiomics
US-based radiomics showed better predictive ability than MMG-based radiomics model. The hybrid clinicopathological and US + MMG + LR model with improved performance can assist tailored therapeutic strategies.
Authors
- Jiejie Yao (ORCID: https://orcid.org/0000-0002-2437-9444)
- Jianqiao Zhou (ORCID: https://orcid.org/0000-0002-0964-8407)
- Wei Zhou (ORCID: https://orcid.org/0000-0003-2434-4644)
- Anqi Li (ORCID: https://orcid.org/0000-0002-3037-9483)
- Xiaoyu Li (ORCID: https://orcid.org/0000-0002-0153-4536)
- Xiaosong Chen (ORCID: https://orcid.org/0000-0002-3286-0035)
- Weimin Chai (ORCID: https://orcid.org/0000-0002-8538-2698)
Institutions
- Shanghai Jiao Tong University (CN)
- Ruijin Hospital (CN)
Publication Details
- Journal
- European journal of medical research
- Published
- 2025-11-24
- DOI
- https://doi.org/10.1186/s40001-025-03435-0
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00