Machine Learning, Deep Learning, and Closed Loop Devices—Anesthesia Delivery - 12/08/21
, Christine Lee, PhD c, d, Maxime Cannesson, MD, PhD a, bResumen |
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.
El texto completo de este artículo está disponible en PDF.Keywords : Machine learning, Neural networks, Deep learning, Closed loop devices, Artificial intelligence
Esquema
| Financial Disclosures: None. |
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| Conflicts of interest: M. Cannesson is a consultant for Edwards Lifesciences and Masimo Corp and has funded research from Edwards Lifesciences and Masimo. He also is the founder of Sironis, owns patents, and receives royalties for closed loop hemodynamic management that have been licensed to Edwards Lifesciences. His department receives funding from the National Institutes of Health (NIH) (R01GM117622; R01 NR013012; U54HL119893; 1R01HL144692). C. Lee is an employee of Edwards Lifesciences. |
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| Clinical trial number: Not Applicable. |
Vol 39 - N° 3
P. 565-581 - septembre 2021 Regresar al númeroBienvenido a EM-consulte, la referencia de los profesionales de la salud.
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