Artificial Intelligence-Enabled Electrocardiograms: Do 15-Lead Studies Improve Model Performance?

Abstract

Authors

• Joshua Mayourian
  Department of Cardiology (J.M., S.J.G., T.G., A.D., M.E.A., J.K.T.), Boston Children's Hospital, MA.
• Sunil Ghelani
  From the Institutes of Health Informatics (T.Y.) and Cardiovascular Science (M.Q., J.A.S., V.M.), University College London, 20c Guilford Street, London WC1N 1DZ, England; Department of Cardiology, Boston Children's Hospital, Boston, Mass (N.S.C., G.F.M., S.G., D.S., R.H.R.); Department of Pediatrics, University of Michigan, Ann Arbor, Mich (A.L.D.); Division of Cardiology, The Children's Hospital of Philadelphia, Philadelphia, Pa (M.A.F.); Department of Radiology, Nationwide Children's Hospital, Columbus, Ohio (R.K.); Department of Diagnostic Imaging, Hospital for Sick Children, Toronto, Canada (C.Z.L.); Department of Pediatrics, Ann and Robert H Lurie Children's Hospital of Chicago, Chicago, Ill (J.D.R.); Department of Pediatric Cardiology, Emory University School of Medicine, Atlanta, Ga (T.C.S.); and Department of Cardiology, Texas Children's Hospital, Houston, Tex (J.W.).
• John K Triedman
  Department of Cardiology (J.M., S.J.G., T.G., A.D., M.E.A., J.K.T.), Boston Children's Hospital, MA.

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