Predictors of mortality by an artificial intelligence enhanced electrocardiogram model for cardiac amyloidosis.

Journal: ESC heart failure
PMID: 39215684

Abstract

AIMS: We aim to determine if our previously validated, diagnostic artificial intelligence (AI) electrocardiogram (ECG) model is prognostic for survival among patients with cardiac amyloidosis (CA).

Authors

  • Jennifer M Amadio
    Department of Cardiovascular Diseases, Mayo Clinic, Rochester, Minnesota, USA.
  • Martha Grogan
    Department of Cardiovascular Medicine, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
  • Eli Muchtar
    Division of Hematology, Mayo Clinic, Rochester, Minnesota, USA.
  • Francisco Lopez-Jimenez
    Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA.
  • Zachi I Attia
    Department of Cardiovascular Medicine, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
  • Omar AbouEzzeddine
    Department of Cardiovascular Diseases, Mayo Clinic, Rochester, Minnesota, USA.
  • Grace Lin
    Department of Cardiovascular Medicine, Mayo Clinic College of Medicine, Rochester, Minnesota.
  • Surendra Dasari
    Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA.
  • Suraj Kapa
    Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
  • Daniel D Borgeson
    Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN.
  • Paul A Friedman
    Department of Cardiovascular Medicine, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
  • Morie A Gertz
    Division of Hematology, Mayo Clinic, Rochester, Minnesota, USA.
  • Dennis H Murphree
    Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, Minnesota, USA.
  • Angela Dispenzieri
    Division of Hematology, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.

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