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

Crossref DOI link: https://doi.org/10.1007/s10549-022-06614-3

Published Online: 2022-05-16

Published Print: 2022-07

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

McGuinness, Julia E. https://orcid.org/0000-0001-5292-1440
Ro, Vicky

Mutasa, Simukayi

Pan, Samuel

Hu, Jianhua

Trivedi, Meghna S.

Accordino, Melissa K.

Kalinsky, Kevin

Hershman, Dawn L.

Ha, Richard S.

Crew, Katherine D.
Funding

Funding for this research was provided by:

Conquer Cancer Foundation (2021YIA-6088880692)

National Cancer Institute (R01 CA226060-04SI)

National Institutes of Health (R38 CA231577, P30 CA013696)

U.S. National Library of Medicine (T15 LM007079-29)

Irving Medical Center, Columbia University (Velocity Pilot Grant)
License Information

Text and Data Mining valid from 2022-05-16

Version of Record valid from 2022-05-16
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Article History

Received: 26 January 2022

Accepted: 18 April 2022

First Online: 16 May 2022

Declarations

:

: JEM, VR, SM, SP, JH, MST, MKA, DLH, RSH, KDC declare no conflict of interest. KK declares the following potential conflicts of interest: Medical Advisor—Immunomedics, Pfizer, Novartis, Eisai, Eli-Lilly, Amgen, Immunomedics, Merck, Seattle Genetics, and Astra Zeneca; Institutional Support—Immunomedics, Novartis, Incyte, Genentech/Roche, Eli-Lilly, Pfizer, Calithera Biosciences, Acetylon, Seattle Genetics, Amgen, Zentalis Pharmaceuticals, and CytomX Therapeutics; Speakers Bureau—Eli-Lilly; Spouse—Array Biopharma, Pfizer, Grail.

: This study was approved by the Institutional Review Board at CUIMC.

: This study was a retrospective cohort study, and consent to participate was not applicable.

: Not applicable to this publication.

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