Risk Stratification of CABG Patients Using an Artificial Intelligence ECG-Derived Age.

Abstract

Authors

• Tedy Sawma
  Department of Cardiovascular Surgery, Mayo Clinic, Rochester, Minn.
• Arman Arghami
  Department of Cardiovascular Surgery, Mayo Clinic, Rochester, Minn.
• Hartzell V Schaff
  Department of Cardiovascular Surgery, Mayo Clinic, Rochester, Minn. Electronic address: Schaff@mayo.edu.
• Masoomeh Aslahishahri
  Department of Biostatistics and Epidemiology.
• Kathryn E Mangold
  Department of Cardiovascular Medicine, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
• Joseph A Dearani
  From Divisions of Cardiovascular Surgery (R.M.S., A.T., H.M.B., R.C.D., J.A.D.), Anesthesiology (W.M.), Cardiovascular Diseases (R.A.N., H.I.M., M.E.-S.), and Biomedical Statistics and Informatics (Z.L.), Mayo Clinic, Rochester, MN.
• John M Stulak
  Department of Cardiac Surgery, Mayo Clinic School of Medicine, Rochester, Minnesota, USA.
• Gabor Bagameri
  Department of Cardiovascular Surgery, Mayo Clinic, Rochester, Minnesota, USA.
• Mauricio A Villavicencio
  Department of Cardiovascular Surgery, Mayo Clinic, Rochester, Minnesota, USA.
• Kevin L Greason
  Department of Cardiovascular Surgery, Mayo Clinic, Rochester, Minnesota, USA.
• Francisco Lopez-Jimenez
  Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA.
• Paul Friedman
  Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA.
• Zachi Attia
  Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA.
• Juan A Crestanello
  Department of Cardiovascular Surgery (A.A., J.A.C.), Mayo Clinic, Rochester, MN.

Keywords

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