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

  • Patient Safety in Anesthesia (SJ Brull and JR Renew, Section Editors)
  • Published:
Current Anesthesiology Reports Aims and scope Submit manuscript

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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Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

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Authors and Affiliations

  1. Department of Anesthesiology and Perioperative Medicine, Brussels, UZ, Belgium

    Domien Vanhonacker, Michaël Verdonck & Hugo Nogueira Carvalho

  2. Department of Anaesthesia, St George’s University Hospitals, NHS Foundation Trust, London, UK

    Hugo Nogueira Carvalho

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Domien Vanhonacker declares having received fees from Edwards Lifesciences (Irvine CA, USA) for lectures, presentations, and educational events.

Hugo Carvalho and Michael Verdonck declare that they have no conflict of interest.

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Vanhonacker, D., Verdonck, M. & Nogueira Carvalho, H. Impact of Closed-Loop Technology, Machine Learning, and Artificial Intelligence on Patient Safety and the Future of Anesthesia. Curr Anesthesiol Rep 12, 451–460 (2022). https://doi.org/10.1007/s40140-022-00539-9

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  • DOI: https://doi.org/10.1007/s40140-022-00539-9

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