The Evolving Landscape of Deep Learning in Breast Cancer Imaging: A Bibliometric Study of Segmentation, Detection, and Diagnostic Research From 2006 to 2025.
- DOI
- 10.1177/10732748261469229
- Published
- 2026 Jan-Dec
- Container
- Cancer control : journal of the Moffitt Cancer Center
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1177/10732748261469229,
title = {The Evolving Landscape of Deep Learning in Breast Cancer Imaging: A Bibliometric Study of Segmentation, Detection, and Diagnostic Research From 2006 to 2025.},
author = {Zeng S and Wang L and Zhang Y and Deng Y and Shen X and Li Y},
year = {2026},
journal = {Cancer control : journal of the Moffitt Cancer Center},
doi = {10.1177/10732748261469229},
url = {https://doi.org/10.1177/10732748261469229}
}RIS
TY - JOUR TI - The Evolving Landscape of Deep Learning in Breast Cancer Imaging: A Bibliometric Study of Segmentation, Detection, and Diagnostic Research From 2006 to 2025. AU - Zeng S AU - Wang L AU - Zhang Y AU - Deng Y AU - Shen X AU - Li Y PY - 2026 JO - Cancer control : journal of the Moffitt Cancer Center DO - 10.1177/10732748261469229 UR - https://doi.org/10.1177/10732748261469229 ER -
APA
S, Z., L, W., Y, Z., Y, D., X, S., & Y, L. (2026). The Evolving Landscape of Deep Learning in Breast Cancer Imaging: A Bibliometric Study of Segmentation, Detection, and Diagnostic Research From 2006 to 2025.. Cancer control : journal of the Moffitt Cancer Center. https://doi.org/10.1177/10732748261469229
Source records
- pubmed · retrieved 2026-09-25T12:53:45.482Z