Image analysis with deep learning to predict breast cancer grade, ER status, histologic subtype, and intrinsic subtype-Reference-Cited by-同舟云学术

Image analysis with deep learning to predict breast cancer grade, ER status, histologic subtype, and intrinsic subtype

Published:2018-09-03 Issue:1 Volume:4 Page:
ISSN:2374-4677
Container-title:npj Breast Cancer
language:en
Short-container-title:npj Breast Cancer

Author:

Couture Heather D.,Williams Lindsay A.,Geradts Joseph,Nyante Sarah J.,Butler Ebonee N.,Marron J. S.,Perou Charles M.,Troester Melissa A.,Niethammer Marc

Publisher

Springer Science and Business Media LLC

Subject

Pharmacology (medical),Radiology, Nuclear Medicine and imaging,Oncology

Link

http://www.nature.com/articles/s41523-018-0079-1.pdf

Reference40 articles.

1. Dunnwald, L. K., Rossing, M. A. & Li, C. I. Hormone receptor status, tumor characteristics, and prognosis: a prospective cohort of breast cancer patients. Breast Cancer Res. 9, R6 (2007).

2. Parker, J. S. et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J. Clin. Oncol. 27, 1160–1167 (2009).

3. Sparano, J. A. & Paik, S. Development of the 21-gene assay and its application in clinical practice and clinical trials. J. Clin. Oncol. 26, 721–728 (2008).

4. Carlson, J. J. & Roth, J. A. The impact of the Oncotype Dx breast cancer assay in clinical practice: a systematic review and meta-analysis. Breast Cancer Res. Treat. 141, 13–22 (2013).

5. Beck, A. H. et al. Systematic analysis of breast cancer morphology uncovers stromal features associated with survival. Sci. Transl. Med. 3, 108ra113 (2011).

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