Automated Triage of Screening Breast MRI Examinations in High-Risk Women Using an Ensemble Deep Learning Model.

Abstract

Authors

• Arka Bhowmik
  From the Departments of Radiology.
• Natasha Monga
  From the Departments of Radiology.
• Kristin Belen
  From the Departments of Radiology.
• Keitha Varela
  From the Departments of Radiology.
• Varadan Sevilimedu
  From the Department of Radiology (R.K.G.D., P.I.C.A., M.T., N.G., K.J., H.H.), Human Pathology and Pathogenesis Program, Center for Molecular Oncology (A.L.), Department of Strategy and Innovation (H.N., P.R., L.G., K.N.), and Biostatistics Service, Department of Epidemiology and Biostatistics (C.J.F., N.S., V.S.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; and School of Computing, Queens University, Kingston, Canada (K.L., K.B., F.Z., A.S.).
• Sunitha B Thakur
• Danny F Martinez
  Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
• Elizabeth J Sutton
  Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA. suttone@mskcc.org.
• Katja Pinker
  Department of Radiology, Columbia University, Vagelos College of Physicians and Surgeons, New York, New York, USA.
• Sarah Eskreis-Winkler
  Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th Street, New York, NY, 10065, USA.

Keywords

External Resources