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Artificial Intelligence in Anesthesiology: Current Techniques, Clinical Applications, and Limitations.

Publication ,  Journal Article
Hashimoto, DA; Witkowski, E; Gao, L; Meireles, O; Rosman, G
Published in: Anesthesiology
February 2020

Artificial intelligence has been advancing in fields including anesthesiology. This scoping review of the intersection of artificial intelligence and anesthesia research identified and summarized six themes of applications of artificial intelligence in anesthesiology: (1) depth of anesthesia monitoring, (2) control of anesthesia, (3) event and risk prediction, (4) ultrasound guidance, (5) pain management, and (6) operating room logistics. Based on papers identified in the review, several topics within artificial intelligence were described and summarized: (1) machine learning (including supervised, unsupervised, and reinforcement learning), (2) techniques in artificial intelligence (e.g., classical machine learning, neural networks and deep learning, Bayesian methods), and (3) major applied fields in artificial intelligence.The implications of artificial intelligence for the practicing anesthesiologist are discussed as are its limitations and the role of clinicians in further developing artificial intelligence for use in clinical care. Artificial intelligence has the potential to impact the practice of anesthesiology in aspects ranging from perioperative support to critical care delivery to outpatient pain management.

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Published In

Anesthesiology

DOI

EISSN

1528-1175

Publication Date

February 2020

Volume

132

Issue

2

Start / End Page

379 / 394

Location

United States

Related Subject Headings

  • Neural Networks, Computer
  • Monitoring, Intraoperative
  • Machine Learning
  • Humans
  • Deep Learning
  • Artificial Intelligence
  • Anesthesiology
  • Anesthesiology
  • 3202 Clinical sciences
  • 1103 Clinical Sciences
 

Citation

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Hashimoto, D. A., Witkowski, E., Gao, L., Meireles, O., & Rosman, G. (2020). Artificial Intelligence in Anesthesiology: Current Techniques, Clinical Applications, and Limitations. Anesthesiology, 132(2), 379–394. https://doi.org/10.1097/ALN.0000000000002960
Hashimoto, Daniel A., Elan Witkowski, Lei Gao, Ozanan Meireles, and Guy Rosman. “Artificial Intelligence in Anesthesiology: Current Techniques, Clinical Applications, and Limitations.Anesthesiology 132, no. 2 (February 2020): 379–94. https://doi.org/10.1097/ALN.0000000000002960.
Hashimoto DA, Witkowski E, Gao L, Meireles O, Rosman G. Artificial Intelligence in Anesthesiology: Current Techniques, Clinical Applications, and Limitations. Anesthesiology. 2020 Feb;132(2):379–94.
Hashimoto, Daniel A., et al. “Artificial Intelligence in Anesthesiology: Current Techniques, Clinical Applications, and Limitations.Anesthesiology, vol. 132, no. 2, Feb. 2020, pp. 379–94. Pubmed, doi:10.1097/ALN.0000000000002960.
Hashimoto DA, Witkowski E, Gao L, Meireles O, Rosman G. Artificial Intelligence in Anesthesiology: Current Techniques, Clinical Applications, and Limitations. Anesthesiology. 2020 Feb;132(2):379–394.

Published In

Anesthesiology

DOI

EISSN

1528-1175

Publication Date

February 2020

Volume

132

Issue

2

Start / End Page

379 / 394

Location

United States

Related Subject Headings

  • Neural Networks, Computer
  • Monitoring, Intraoperative
  • Machine Learning
  • Humans
  • Deep Learning
  • Artificial Intelligence
  • Anesthesiology
  • Anesthesiology
  • 3202 Clinical sciences
  • 1103 Clinical Sciences