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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.

Alex NovakSarim AtherAvneet GillPeter AylwardGiles MaskellGordon W CowellAbdala Trinidad Espinosa MorgadoTom DugganMelissa KeevilOliva GordonOsama AkramaElizabeth BelcherRhona TaberhamRob HallifaxJasdeep BahraAbhishek BanerjiJon BaileyAntonia JamesAli AnsaripourNathan SpenceJohn WrightsonWaqas JarralSteven BarrySaher BhattiKerry AstleyAmied ShadmaanSharon GhelmanAlec BaenenJason OkeClaire BloomfieldMark BeggsFergus Gleeson
Published in: Emergency medicine journal : EMJ (2024)
The study indicates that AI-assisted image interpretation significantly enhances the diagnostic accuracy of clinicians in detecting PTX, particularly benefiting less experienced practitioners. While overall interpretation time remained unchanged, the use of AI improved diagnostic confidence and sensitivity, especially among junior clinicians. These findings underscore the potential of AI to support less skilled clinicians in acute care settings.
Keyphrases
  • artificial intelligence
  • deep learning
  • machine learning
  • acute care
  • palliative care
  • big data
  • primary care
  • magnetic resonance imaging
  • risk assessment
  • contrast enhanced