Use of a convolutional neural network-based mammographic evaluation to predict breast cancer recurrence among women with hormone receptor-positive operable breast cancer

McGuinness, J. E., Ro, V., Mutasa, S., Pan, S., Hu, J., Trivedi, M. S., Accordino, M. K., Kalinsky, K., Hershman, D. L., Ha, R. S., & Crew, K. D. (2022). Use of a convolutional neural network-based mammographic evaluation to predict breast cancer recurrence among women with hormone receptor-positive operable breast cancer. Breast Cancer Research and Treatment, 194(1), 35–47. https://doi.org/10.1007/s10549-022-06614-3
Authors:
Julia E. McGuinness
Vicky Ro
Simukayi Mutasa
Samuel Pan
Jianhua Hu
Meghna S. Trivedi
Melissa K. Accordino
Kevin Kalinsky
Dawn L. Hershman
Richard S. Ha
Katherine D. Crew
Affiliated Authors:
Julia E. McGuinness
Vicky Ro
Simukayi Mutasa
Samuel Pan
Jianhua Hu
Meghna S. Trivedi
Melissa K. Accordino
Dawn L. Hershman
Richard S. Ha
Katherine D. Crew
Columbia Affiliation:
Subjects:
Breast Neoplasms (MeSH)
Author Keywords:
convolutional neural networks
breast cancer
endocrine therapy
imaging-based biomarker
mammography
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Publication Type:
Article
Unique ID:
10.1007/s10549-022-06614-3
PMID:
35575954
DOI:
10.1007/s10549-022-06614-3
Journal:
Breast Cancer Research and Treatment
Publication Date:
Data Source:
Scopus
Source Link:
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Record Created: