Addressing Clinical Ambiguity in Breast Density Assessment: A Hybrid Multi-View Deep Learning Framework for BI-RADS B vs. C Classification.
- DOI
- 10.3390/diagnostics16132044
- Published
- 2026 Jun 30
- Container
- Diagnostics (Basel, Switzerland)
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/diagnostics16132044,
title = {Addressing Clinical Ambiguity in Breast Density Assessment: A Hybrid Multi-View Deep Learning Framework for BI-RADS B vs. C Classification.},
author = {Triqui B and Kaid-Slimane H},
year = {2026},
journal = {Diagnostics (Basel, Switzerland)},
doi = {10.3390/diagnostics16132044},
url = {https://doi.org/10.3390/diagnostics16132044}
}RIS
TY - JOUR TI - Addressing Clinical Ambiguity in Breast Density Assessment: A Hybrid Multi-View Deep Learning Framework for BI-RADS B vs. C Classification. AU - Triqui B AU - Kaid-Slimane H PY - 2026 JO - Diagnostics (Basel, Switzerland) DO - 10.3390/diagnostics16132044 UR - https://doi.org/10.3390/diagnostics16132044 ER -
APA
B, T., & H, K. (2026). Addressing Clinical Ambiguity in Breast Density Assessment: A Hybrid Multi-View Deep Learning Framework for BI-RADS B vs. C Classification.. Diagnostics (Basel, Switzerland). https://doi.org/10.3390/diagnostics16132044
Source records
- pubmed · retrieved 2026-09-25T21:15:24.825Z