Clinical utility of a deep-learning mortality prediction model for cardiac surgery decision making.

Journal: The Journal of thoracic and cardiovascular surgery
Published Date: Feb 2, 2023

Abstract

OBJECTIVES: The aim of this study using decision curve analysis (DCA) was to evaluate the clinical utility of a deep-learning mortality prediction model for cardiac surgery decision making compared with the European System for Cardiac Operative Risk Evaluation (EuroSCORE) II and to 2 machine-learning models.

Authors

  • Nicolas Allou
    Réanimation Polyvalente, Centre Hospitalier Universitaire Félix Guyon, Saint-Denis, France.
  • Jérôme Allyn
    Réanimation Polyvalente, Centre Hospitalier Universitaire Félix Guyon, Saint-Denis, France.
  • Sophie Provenchere
    Département d'Anesthésie Réanimation, APHP, CHU Bichat-Claude Bernard, Paris, France.
  • Benjamin Delmas
    Anesthesia and Cardiac Surgery, Félix Guyon University Hospital, Saint Denis, France.
  • Eric Braunberger
    Anesthesia and Cardiac Surgery, Félix Guyon University Hospital, Saint Denis, France.
  • Matthieu Oliver
    Methodological Support Unit, Reunion University Hospital, Saint-Denis, France. matthieu.oliver@chu-reunion.fr.
  • Jean Louis De Brux
    Cardiac Surgery, Angers University Hospital, Angers, France.
  • Cyril Ferdynus
    Unité de Soutien Méthodologique, CHU de La Réunion, Saint-Denis, France.

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