Breast cancer molecular subtype classifier that incorporates MRI features.

@article{Sutton2016BreastCM,
  title={Breast cancer molecular subtype classifier that incorporates MRI features.},
  author={Elizabeth J. Sutton and Brittany Z Dashevsky and Jung Hun Oh and Harini Veeraraghavan and Aditya P. Apte and Sunitha B Thakur and Elizabeth A. Morris and Joseph O. Deasy},
  journal={Journal of magnetic resonance imaging : JMRI},
  year={2016},
  volume={44 1},
  pages={
          122-9
        }
}
PURPOSE To use features extracted from magnetic resonance (MR) images and a machine-learning method to assist in differentiating breast cancer molecular subtypes. MATERIALS AND METHODS This retrospective Health Insurance Portability and Accountability Act (HIPAA)-compliant study received Institutional Review Board (IRB) approval. We identified 178 breast cancer patients between 2006-2011 with: 1) ERPR + (n = 95, 53.4%), ERPR-/HER2 + (n = 35, 19.6%), or triple negative (TN, n = 48, 27.0… CONTINUE READING

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