Addressing Clinical Ambiguity in Breast Density Assessment: A Hybrid Multi-View Deep Learning Framework for BI-RADS B vs. C Classification.

Triqui B, Kaid-Slimane H

Open source

DOI
10.3390/diagnostics16132044
Published
2026 Jun 30
Container
Diagnostics (Basel, Switzerland)
Publisher
Not recorded
Open access
yes

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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

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