Management algorithms and artificial intelligence systems for cardiopulmonary bypass.

Journal: Perfusion
PMID:

Abstract

This article introduces management algorithms to support operators in choosing the best strategy for metabolic management during cardiopulmonary bypass using artificial intelligence systems. We developed algorithms for the identification of the optimal way for assessing metabolic parameters. Different management algorithms for extracorporeal procedures interfaced with metabolic monitoring systems already exist on the market and are applied in clinical practice. These algorithms could provide guidance for selecting the best metabolic strategy with the aim at reducing human error and optimizing management.

Authors

  • Ignazio Condello
    Department of Cardiac Surgery, Anthea Hospital - GVM Care & Research, Bari, Italy.
  • Giuseppe Santarpino
    Paracelsus Medical University, Klinikum Nürnberg. Nuremberg, Germany.
  • Giuseppe Nasso
    Department of Cardiac Surgery, Anthea Hospital - GVM Care & Research, Bari, Italy.
  • Marco Moscarelli
    Department of Cardiac Surgery, Anthea Hospital - GVM Care & Research, Bari, Italy.
  • Flavio Fiore
    Department of Cardiac Surgery, Anthea Hospital - GVM Care & Research, Bari, Italy.
  • Giuseppe Speziale
    Department of Cardiac Surgery, Santa Maria Hospital-GVM Care & Research, Bari, Italy.