Guidance for reporting artificial intelligence technology evaluations for ultrasound scanning in regional anaesthesia ( <scp>GRAITE</scp> ‐ <scp>USRA</scp> ): an international multidisciplinary consensus reporting framework
The GRAITE-USRA reporting guideline provides a minimum set of recommendations for artificial intelligence-related research for ultrasound scanning in regional anaesthesia. Its adoption will promote consistent reporting standards, enhance transparency, improve study reproducibility and ultimately support the effective integration of evidence into clinical practice.
Authors
- David W. Hewson (ORCID: https://orcid.org/0000-0002-5314-8522)
- M. D. Wiles (ORCID: https://orcid.org/0000-0003-2299-0060)
- Professor Gary S. Collins (ORCID: https://orcid.org/0000-0002-2772-2316)
- James Simeon Bowness (ORCID: https://orcid.org/0000-0002-8665-1984)
- Jenny Ferry (ORCID: https://orcid.org/0000-0002-9034-8478)
- Xiaoxi Zhang (ORCID: https://orcid.org/0000-0002-7071-5285)
- Yi Zhao (ORCID: https://orcid.org/0000-0003-2534-6465)
- Michael Tomaschek
Institutions
- Nottingham University Hospitals NHS Trust (GB)
- University College London Hospitals NHS Foundation Trust (GB)
- University of Nottingham (GB)
- NHS Ayrshire and Arran (GB)
- Nuffield Orthopaedic Centre (GB)
- Aneurin Bevan University Health Board (GB)
- University of Oxford (GB)
- Sheffield Teaching Hospitals NHS Foundation Trust (GB)
- King's College Hospital NHS Foundation Trust (GB)
- Media Working Group (US)
- Newham University Hospital (GB)
- Chelsea and Westminster Hospital (GB)
- University College London (GB)
- Sheffield Hallam University (GB)
Publication Details
- Journal
- Anaesthesia
- Published
- 2025-09-18
- DOI
- https://doi.org/10.1111/anae.16733
- Primary Topic
- Cardiac, Anesthesia and Surgical Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 0.00