Promoting head CT exams in the emergency department triage using a machine learning model.

Journal: Neuroradiology
Published Date: Oct 10, 2019

Abstract

PURPOSE: In this study, we aimed to develop a novel prediction model to identify patients in need of a non-contrast head CT exam during emergency department (ED) triage.

Authors

  • Eyal Klang
    Division of Data-Driven and Digital Medicine (D3M), Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Yiftach Barash
    Department of Diagnostic Imaging, Chaim Sheba Medical Center, Tel Hashomer, Israel.
  • Shelly Soffer
    From the Department of Diagnostic Imaging, Sheba Medical Center, Emek HaEla St 1, Ramat Gan, Israel (S.S., M.M.A., E.K.); Faculty of Engineering, Department of Biomedical Engineering, Medical Image Processing Laboratory, Tel Aviv University, Tel Aviv, Israel (A.B., H.G.); and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel (S.S., O.S.).
  • Sigalit Bechler
    Intuit, HaHarash St.4, Building C 2nd floor, 4524075, Hod HaSharon, Israel.
  • Yehezkel S Resheff
    Intuit, HaHarash St.4, Building C 2nd floor, 4524075, Hod HaSharon, Israel.
  • Talia Granot
    Intuit, HaHarash St.4, Building C 2nd floor, 4524075, Hod HaSharon, Israel.
  • Moni Shahar
    Intuit, HaHarash St.4, Building C 2nd floor, 4524075, Hod HaSharon, Israel.
  • Maximiliano Klug
    Department of Diagnostic Imaging, Sheba Medical Center, Emek HaEla St 1, Ramat Gan, Israel.
  • Gennadiy Guralnik
    Sackler School of Medicine, Tel Aviv University, Einstein St 68, Tel Aviv, Israel.
  • Eyal Zimlichman
    Sheba Medical Center, Tel Hashomer, Israel.
  • Eli Konen

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