Impact of Closed-Loop Technology, Machine Learning, and Artificial Intelligence on Patient Safety and the Future of Anesthesia

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8 Citaten (Scopus)

Samenvatting

Purpose of Review
The purpose of the present narrative review is to look at the present and future impact of closed-loop technology, artificial intelligence (AI), and machine learning (ML) on anesthesia and patient safety.

Recent Findings
AI and ML are omnipresent and encountered daily without one’s awareness. More and more promising AI-guided tools are being developed to help anesthesiologists provide better patient care. Some of these applications are already at par or outperforming clinicians in concrete tasks, although significant work is still needed for their effective and safe integration into clinical practice. Additionally, major ethical and legal questions need to be addressed before such algorithms can become mainstream.

Summary
Despite the challenges ahead, the implementation of AI-driven technologies has significant potential to positively complement modern anesthesia care, and as such, significantly improve patient safety.
Originele taal-2English
Pagina's (van-tot)451–460
Aantal pagina's10
TijdschriftCurrent Anesthesiology Reports
Volume12
Nummer van het tijdschrift4
DOI's
StatusPublished - dec. 2022

Bibliografische nota

Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Copyright:
Copyright 2022 Elsevier B.V., All rights reserved.

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