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This scoping review examines necessary radiography curriculum adjustments for artificial intelligence (AI) integration. Findings will guide educational changes to ensure radiographers are prepared for AI-assisted healthcare.

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Area of Science:

  • Radiography
  • Medical Imaging
  • Health Professions Education

Background:

  • Artificial intelligence (AI) is increasingly used in radiography practice.
  • The role of radiographers is evolving with AI integration.
  • Educational modifications are needed for AI adoption in radiography.

Purpose of the Study:

  • To explore and synthesize literature on radiography curriculum adjustments for AI.
  • To prepare radiography students for AI-assisted healthcare environments.

Main Methods:

  • Scoping review using Joanna Briggs Institute methodology.
  • Searches conducted in Scopus, EBSCOhost, PubMed, and Web of Science.
  • Independent review by two reviewers, with conflicts resolved by a third.

Main Results:

  • Initial search yielded 2224 records; 1930 articles are undergoing title/abstract screening.
  • PRISMA-ScR checklist will guide results reporting.
  • Data analysis will be presented in tabular and narrative forms.

Conclusions:

  • Mapping evidence on curriculum adjustments is crucial for AI integration in radiography.
  • Adapting education ensures competent and safe radiographer practice with AI.
  • Findings will inform curriculum development for future radiographers.