A machine learning approach to radiogenomics of breast cancer: a study of 922 subjects and 529 DCE-MRI features
Author:
Funder
U.S. Department of Health & Human Services | National Institutes of Health
Publisher
Springer Science and Business Media LLC
Subject
Cancer Research,Oncology
Link
http://www.nature.com/articles/s41416-018-0185-8.pdf
Reference34 articles.
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3. Fan, M. et al. Radiomic analysis reveals DCE-MRI features for prediction of molecular subtypes of breast cancer. PLoS ONE. 12, e0171683 (2017).
4. Wan, T. et al. A radio-genomics approach for identifying high risk estrogen receptor-positive breast cancers on DCE-MRI: preliminary results in predicting oncotypeDX risk scores. Sci. Rep. 6, 21394 (2016).
5. Ashraf, A. B. et al. Identification of intrinsic imaging phenotypes for breast cancer tumors: preliminary associations with gene expression profiles. Radiology 272, 374–384 (2014).
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