Overview of medical radiation students and graduates artificial intelligence readiness for clinical practice and integration

Introduction: The evolving complex artificial intelligence (AI) technology in medical imaging is no longer a prospect, with applications among other spanning across image acquisition and optimisation, reconstruction, dose-optimisation and interpretation.1

The Medical Radiation Practice Board of Australia (MRPBA)2 highlights the need for practitioners to maintain control over AI-supported technologies to ensure safe clinical use. Educational institutions must lead in equipping future medical imaging professionals with the knowledge, skills and clinical experience needed to work effectively with AI. This study explores the level of readiness of final-year students and graduate professionals' knowledge and competencies in AI technology.

Methods: This study entailed cross-sectional survey. Eligible participants were Australian final-year students or recent graduates (≤18 months post-qualification) from accredited Australian medical radiation science programs. The questionnaire entailed demographic questions, 22 questions from the validated MAIRS-MS tool and open-ended item response. Survey was administered using QualtricsXM.

Results: Data collection is currently in progress. It is anticipated that this study will inform on current trends on of AI content /knowledge integration in course offerings, the level of preparedness and impact on AI integrated medical imaging practice contexts.

Discussion: The discussion will be based on the findings. It is envisaged that the current study will inform curriculum development and continuing professional education strategies, to better align with the MRPBA's recommendations for safe and effective AI integration.

Conclusion: A baseline profile to inform on curriculum design and workplace place requirements in alignment with the regulatory AI-related MRPBA's professional capabilities framework.