The Evolving Role of Machine Learning in the Analysis of Outcomes After Pediatric and Congenital Cardiac Surgery.

Abstract

Authors

• Jeffrey Phillip Jacobs
  Congenital Heart Center Division of Cardiothoracic Surgery Departments of Surgery and Pediatrics University of Florida, 1600 SW Archer Rd, Gainesville, FL 32608. Electronic address: jeffreyjacobs@ufl.edu.
• S Ram Kumar
  Division of Cardiothoracic Surgery Children's Nebraska University of Nebraska Medical Center Omaha, Nebraska.
• David M Overman
  Division of Cardiovascular Surgery, Mayo Clinic-Children's Minnesota Cardiovascular Collaborative, Minneapolis, Minnesota.
• 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.
• Jennifer C Romano
  Department of Cardiac Surgery, University of Michigan, Ann Arbor, Michigan.

Keywords

External Resources