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TCGA Breast Phenotype Research Group Publications

  • Burnside ES, Drukker K, Li H, Bonaccio E, Zuley M, Ganott M, Net JM, Sutton EJ, Brandt KR, Whitman GJ, Conzen SD, Lan L, Ji Y,10, Zhu Y,Jaffe CC, Huang EP, Freymann JB, Kirby JS, Morris EA, Giger ML. Guo W, Li H, Zhu Y, Lan L, Yang S, Drukker K, Morris E, Burnside E, Whitman G, Giger ML*, Ji Y*:  Prediction of clinical phenotypes in invasive breast carcinomas from the integration of radiomics and genomics data.  J Medical Imaging 2(4), 041007 (Oct-Dec 2015).
  • Burnside E, Drukker K, Li H, Bonaccio E, Zuley M, Ganott M, Net JM, Sutton E, Brandt K, Whitman G, Conzen S, Lan L, Ji Y, Zhu Y, Jaffe C, Huang E, Freymann J, Kirby J, Morris EA*, Giger ML*:  Using computer-extracted image phenotypes from tumors on breast magnetic resonance imaging MRI to predict breast cancer pathologic stage. Cancer . 2015 Nov 30. doi: 10.1002/cncr.29791, 2015. (paper)
  • Zhu Y, Li H, Guo W, Drukker K, Lan L, Giger ML*, Ji Y*:  Deciphering genomic underpinnings of quantitative MRI-based radiomic phenotypes of invasive breast carcinoma.  Nature – Scientific Reports 5:17787. doi: 10.1038/srep17787, 2015.
  • Li H, Zhu Y, Burnside ES, …. Perou CM, Ji Y*, Giger ML*:  MRI radiomics signatures for predicting the risk of breast cancer recurrence as given by research versions of gene assays of MammaPrint, Oncotype DX, and PAM50.  Radiology DOI: http://dx.doi.org/10.1148/radiol.2016152110, 2016.
  • Li H, Zhu Y, Burnside ES, …. Perou CM, Ji Y, Giger ML:  Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA Dataset. npj Breast Cancer (2016) 2, 16012; doi:10.1038/npjbcancer.2016.12; published online 11 May 2016.

Publications written by other members of the research community can be found on our TCIA Publications page.  Please contact us at help@cancerimagingarchive.net if you have a publication you would like us to add.

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