Diagnostic Accuracy and Failure Mode Analysis of a Deep Learning Algorithm for the Detection of Intracranial Hemorrhage.

Journal: Journal of the American College of Radiology : JACR
Published Date: Apr 3, 2021

Abstract

OBJECTIVE: To determine the institutional diagnostic accuracy of an artificial intelligence (AI) decision support systems (DSS), Aidoc, in diagnosing intracranial hemorrhage (ICH) on noncontrast head CTs and to assess the potential generalizability of an AI DSS.

Authors

  • Andrew F Voter
    Department of Biomolecular Chemistry , University of Wisconsin School of Medicine and Public Health , Madison , Wisconsin 53706 , United States.
  • Ece Meram
    Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin.
  • John W Garrett
    From the Departments of Medical Physics (R.Z., X.T., C.Z., D.G., J.W.G., K.L., S.B.R., G.H.C.) and Radiology (M.L.S., J.W.G., K.L., S.B.R., G.H.C.), University of Wisconsin-Madison School of Medicine and Public Health, 1111 Highland Ave, Madison, WI 53705; and Department of Radiology, Henry Ford Health System, Detroit, Mich (Z.Q., N.B.B., T.K.S., J.D.N,).
  • John-Paul J Yu
    Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin; Department of Biomedical Engineering, College of Engineering, University of Wisconsin-Madison, Madison, Wisconsin; Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin. Electronic address: jpyu@uwhealth.org.

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