Multimodal deep learning model for prediction of breast cancer recurrence risk and correlation with oncotype DX
This study validated the robust predictive accuracy of the MDL model in identifying high- and low-risk groups for recurrence. The correlations identified between Oncotype DX genes, clinicopathologic features, and deep-learning radiographic features offer novel insights for future biomarker research in breast cancer.
Authors
- Maosheng Xu (ORCID: https://orcid.org/0000-0002-2396-1600)
- Shiwei Wang (ORCID: https://orcid.org/0000-0002-4562-3127)
- Ruixin Zhang (ORCID: https://orcid.org/0000-0002-2463-4839)
- Min Ge
- Kaiting Wang (ORCID: https://orcid.org/0000-0002-4443-2644)
- Chunjie Wang (ORCID: https://orcid.org/0000-0002-6275-361X)
- Tingting Cao (ORCID: https://orcid.org/0000-0002-3688-4691)
- Ce Ci
Institutions
- Zhejiang Chinese Medical University (CN)
- Blood Center of Zhejiang Province (CN)
- Affiliated Hangzhou First People's Hospital, Westlake University, School of Medicine (CN)
Publication Details
- Journal
- Breast Cancer Research
- Published
- 2025-10-14
- DOI
- https://doi.org/10.1186/s13058-025-02129-z
- Citations
- 2
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 4.96
Funders
- Basic Public Welfare Research Program of Zhejiang Province
- Science and Technology Program of Zhejiang Province