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Multimodal AI to simulate medical student competency

The assessment of medical graduate competency is a cornerstone of medical education and a critical safeguard for patient safety. Newly qualified physicians must demonstrate a broad range of skills and knowledge, including diagnostic reasoning, clinical decision-making, communication, procedural skills, and professionalism before independently practicing medicine. Traditional assessment methods often include standardized multiple-choice examinations, objective structured clinical examinations (OSCEs), direct observation of procedural skills (DOPS), and portfolio reviews. While these methods offer valuable insights, they have inherent limitations. Standardized tests may …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Health
School
School of Public Health and Social Work
Research centre(s)
Centre for Data Science

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