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Current Anesthesiology Reports

Erschienen in:

03.10.2022 | Patient Safety in Anesthesia (SJ Brull and JR Renew, Section Editors)

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

verfasst von: Domien Vanhonacker, Michaël Verdonck, Hugo Nogueira Carvalho

Erschienen in: Current Anesthesiology Reports | Ausgabe 4/2022

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Abstract

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.

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Titel: Impact of Closed-Loop Technology, Machine Learning, and Artificial Intelligence on Patient Safety and the Future of Anesthesia
verfasst von: Domien Vanhonacker
Michaël Verdonck
Hugo Nogueira Carvalho
Publikationsdatum: 03.10.2022
Verlag: Springer US
Erschienen in: Current Anesthesiology Reports / Ausgabe 4/2022
Elektronische ISSN: 2167-6275
DOI: https://doi.org/10.1007/s40140-022-00539-9

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