Machine Learning, Deep Learning, and Closed Loop Devices-Anesthesia Delivery.

Journal: Anesthesiology clinics
PMID: 34392886

Abstract

With the tremendous volume of data captured during surgeries and procedures, critical care, and pain management, the field of anesthesiology is uniquely suited for the application of machine learning, neural networks, and closed loop technologies. In the past several years, this area has expanded immensely in both interest and clinical applications. This article provides an overview of the basic tenets of machine learning, neural networks, and closed loop devices, with emphasis on the clinical applications of these technologies.

Authors

  • Theodora Wingert
    University of California Los Angeles, David Geffen School of Medicine, Los Angeles, CA, USA; Department of Anesthesiology and Perioperative Medicine, Ronald Reagan UCLA Medical Center, 757 Westwood Plaza, Suite 3325, Los Angeles, CA 90095-7403, USA. Electronic address: twingert@mednet.ucla.edu.
  • Christine Lee
    Department of Psychiatry and Behavioral Sciences, University of Washington, USA.
  • Maxime Cannesson
    Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.

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