Evaluation of the impact of artificial intelligence-assisted image interpretation on the diagnostic performance of clinicians in identifying pneumothoraces on plain chest X-ray: a multi-case multi-reader study.

Journal: Emergency medicine journal : EMJ
PMID: 39009424

Abstract

BACKGROUND: Artificial intelligence (AI)-assisted image interpretation is a fast-developing area of clinical innovation. Most research to date has focused on the performance of AI-assisted algorithms in comparison with that of radiologists rather than evaluating the algorithms' impact on the clinicians who often undertake initial image interpretation in routine clinical practice. This study assessed the impact of AI-assisted image interpretation on the diagnostic performance of frontline acute care clinicians for the detection of pneumothoraces (PTX).

Authors

  • Alex Novak
    Emergency Medicine Research Oxford, Oxford University Hospitals NHS Foundation Trust, United Kingdom, Oxford.
  • Sarim Ather
    Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom.
  • Avneet Gill
    Ulster University, School of Health Sciences, York St, Northern Ireland.
  • Peter Aylward
    Report and Image Quality Control (RAIQC), London, UK, UK.
  • Giles Maskell
    Royal Cornwall Hospitals NHS Trust, Truro, Cornwall, UK.
  • Gordon W Cowell
    Department of Imaging, Queen Elizabeth University Hospital, Glasgow, UK.
  • Abdala Trinidad Espinosa Morgado
    Emergency Medicine Research Oxford, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
  • Tom Duggan
    Buckinghamshire Healthcare NHS Trust, Amersham, UK.
  • Melissa Keevill
    Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
  • Olivia Gamble
    Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
  • Osama Akrama
    Emergency Department, Royal Berkshire NHS Foundation Trust, Reading, UK.
  • Elizabeth Belcher
    Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
  • Rhona Taberham
    Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
  • Rob Hallifax
    Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
  • Jasdeep Bahra
    Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
  • Abhishek Banerji
    Buckinghamshire Healthcare NHS Trust, Amersham, UK.
  • Jon Bailey
    Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
  • Antonia James
    Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
  • Ali Ansaripour
    Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
  • Nathan Spence
    Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
  • John Wrightson
    Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
  • Waqas Jarral
    Frimley Health NHS Foundation Trust, Frimley, UK.
  • Steven Barry
    Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
  • Saher Bhatti
    Frimley Health NHS Foundation Trust, Frimley, UK.
  • Kerry Astley
    Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
  • Amied Shadmaan
    GE Healthcare Diagnostic Imaging, Little Chalfont, Buckinghamshire, UK.
  • Sharon Ghelman
    GE Healthcare, Chicago, Illinois, USA.
  • Alec Baenen
    GE Healthcare Ltd, Chicago, Illinois, USA.
  • Jason Oke
    Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Claire Bloomfield
    National Consortium of Intelligent Medical Imaging (NCIMI), The University of Oxford, Big Data Institute, Oxford, UK.
  • Hilal Johnson
    University of Oxford, Oxford, Oxfordshire, UK.
  • Mark Beggs
    University of Oxford, Oxford, Oxfordshire, UK.
  • Fergus Gleeson
    Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom.

Keywords

External Resources

Popular Topics
Recent Journals