Artificial intelligence for ultrasound scanning in regional anaesthesia: a scoping review of the evidence from multiple disciplines.

Journal: British journal of anaesthesia
PMID: 38448269

Abstract

BACKGROUND: Artificial intelligence (AI) for ultrasound scanning in regional anaesthesia is a rapidly developing interdisciplinary field. There is a risk that work could be undertaken in parallel by different elements of the community but with a lack of knowledge transfer between disciplines, leading to repetition and diverging methodologies. This scoping review aimed to identify and map the available literature on the accuracy and utility of AI systems for ultrasound scanning in regional anaesthesia.

Authors

  • James S Bowness
    Nuffield Department of Clinical Anaesthesia, University of Oxford, Oxford, UK; Department of Anaesthesia, Aneurin Bevan University Health Board, Newport, UK. Electronic address: james.bowness@jesus.ox.ac.uk.
  • David Metcalfe
    Nuffield Department of Orthopaedics, Rheumatology & Musculoskeletal Sciences, University of Oxford, Oxford, UK; Emergency Medicine Research in Oxford (EMROx), Oxford University Hospitals NHS Foundation Trust, Oxford, UK. Electronic address: https://twitter.com/@TraumaDataDoc.
  • Kariem El-Boghdadly
    Anaesthesia, Guy's and St Thomas' NHS Foundation Trust, London, UK.
  • Neal Thurley
    Bodleian Health Care Libraries, University of Oxford, Oxford, UK.
  • Megan Morecroft
    Intelligent Ultrasound, Cardiff, UK.
  • Thomas Hartley
    School of Engineering, Cardiff University, Cardiff, United Kingdom.
  • Joanna Krawczyk
    Department of Anaesthesia, Aneurin Bevan University Health Board, Newport, UK.
  • J Alison Noble
    Institute of Biomedical Engineering (IBME), University of Oxford, Oxford, England, UK.
  • Helen Higham
    Nuffield Department of Clinical Anaesthesia, University of Oxford, Oxford, UK; Department of Anaesthesia, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.

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