Augmented intelligence in pediatric anesthesia and pediatric critical care.

Journal: Current opinion in anaesthesiology
Published Date:

Abstract

PURPOSE OF REVIEW: Acute care technologies, including novel monitoring devices, big data, increased computing capabilities, machine-learning algorithms and automation, are converging. This enables the application of augmented intelligence for improved outcome predictions, clinical decision-making, and offers unprecedented opportunities to improve patient outcomes, reduce costs, and improve clinician workflow. This article briefly explores recent work in the areas of automation, artificial intelligence and outcome prediction models in pediatric anesthesia and pediatric critical care.

Authors

  • Matthias Görges
    Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia.
  • J Mark Ansermino
    Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada.