Radiographer Education and Learning in Artificial Intelligence (REAL-AI): A survey of radiographers, radiologists, and students' knowledge of and attitude to education on AI.

Journal: Radiography (London, England : 1995)
PMID: 39481214

Abstract

INTRODUCTION: In Autumn 2023, amendments to the Health and Care Professions Councils (HCPC) Standards of Proficiency for Radiographers were introduced requiring clinicians to demonstrate awareness of the principles of AI and deep learning technology, and its application to practice' (HCPC 2023; standard 12.25). With the rapid deployment of AI in departments, staff must be prepared to implement and utilise AI. AI readiness is crucial for adoption, with education as a key factor in overcoming fear and resistance. This survey aimed to assess the current understanding of AI among students and qualified staff in clinical practice.

Authors

  • G Doherty
    Ulster University, School of Health Sciences, Faculty of Life and Health Sciences, Shore Road, Newtownabbey, Northern Ireland, United Kingdom. Electronic address: doherty-g49@ulster.ac.uk.
  • L McLaughlin
    The Discipline of Medical Imaging and Radiation Therapy, University College Cork, College Road, T12 K8AF Cork, Ireland.
  • C Hughes
    Department of Head and Neck Clinical Oncology, The Christie NHS Foundation Trust, Manchester, UK. Electronic address: christopher.hughes@christie.nhs.uk.
  • J McConnell
    Leeds Teaching Hospitals NHS Trust, United Kingdom.
  • R Bond
    Ulster University, Jordanstown Campus, Shore Rd, Newtownabbey BT37 0QB, Northern Ireland, UK.
  • S McFadden
    School of Health Sciences, Ulster University, Belfast, Northern Ireland, BT37OQB, UK.

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