The value of predicting breast cancer with a DBT 2.5D deep learning model
The 2.5D deep learning model based on DBT shows good performance in preoperative breast cancer prediction, with its integration with clinical data further enhancing its effectiveness. The combination of deep learning and radiomics offers a viable approach for early breast cancer diagnosis, supporting the development of more accurate personalized diagnostic and treatment strategies.
Authors
- Huifeng Niu (ORCID: https://orcid.org/0000-0003-1486-1509)
- Xu Han (ORCID: https://orcid.org/0000-0001-9129-3555)
- Ximing Wang (ORCID: https://orcid.org/0000-0001-5136-8057)
- Li Li (ORCID: https://orcid.org/0000-0003-4834-8447)
Institutions
- Shandong Provincial Hospital (CN)
- Shandong First Medical University (CN)
Publication Details
- Journal
- Discover Oncology
- Published
- 2025-03-29
- DOI
- https://doi.org/10.1007/s12672-025-02170-6
- Citations
- 5
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 12.40