Deep Learning vs Traditional Breast Cancer Risk Models to Support Risk-Based Mammography Screening.

Journal: Journal of the National Cancer Institute
Published Date: Oct 6, 2022

Abstract

BACKGROUND: Deep learning breast cancer risk models demonstrate improved accuracy compared with traditional risk models but have not been prospectively tested. We compared the accuracy of a deep learning risk score derived from the patient's prior mammogram to traditional risk scores to prospectively identify patients with cancer in a cohort due for screening.

Authors

  • Constance D Lehman
    From the Division of Breast Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, 55 Fruit St, WAC 240, Boston, MA 02114 (M.B., C.D.L.); and Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Mass (R.B., A.B.Y., N.J.L., L.Y.).
  • Sarah Mercaldo
    Massachusetts General Hospital, Boston, MA, USA.
  • Leslie R Lamb
    Harvard Medical School, Boston, Massachusetts; Massachusetts General Hospital, Boston, Massachusetts.
  • Tari A King
    Harvard Medical School, Surgery, Boston, MA, USA.
  • Leif W Ellisen
    Massachusetts General Hospital, Boston, MA, USA.
  • Michelle Specht
    Massachusetts General Hospital, Boston, MA, USA.
  • Rulla M Tamimi
    Associate Professor, Department of Medicine, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA.

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