Building Confidence in AI-Interpreted CMR.

Abstract

Authors

• João A C Lima
  From the Department of Radiology (B.A.-V.), Bloomberg School of Public Health (E.G.), and Department of Medicine, Cardiology and Radiology (J.A.C.L.), Johns Hopkins University, Baltimore, MD; George Washington University, DC (X.Y.); Office of Biostatistics, NHLBI, NIH, Bethesda, MD (C.O.W.); Department of Preventive Medicine, Northwestern University Medical School, Chicago, IL (K.L.); Department of Cardiology, Wake Forest University Health Sciences, Winston-Salem, NC (W.G.H.); Department of Biostatistics, University of Washington, Seattle (R.M.); Department of Radiology, UCLA School of Medicine, Los Angeles, CA (A.S.G.); Division of Epidemiology and Community Health, University of Minnesota, Minneapolis (A.R.F.); Departments of Medicine and Epidemiology, Columbia University, New York, NY (S.S.); and Radiology and Imaging Sciences, NIH Clinical Center, Bethesda, MD (D.A.B.). jlima@jhmi.edu.
• Bharath Ambale Venkatesh
  The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, The Johns Hopkins Hospital, 1800 Orleans Street, Baltimore, MD 21287 (A.B., G.Z., I.R.K., S.L.Z., B.A.V.). Electronic address: bambale1@jhmi.edu.

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External Resources