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Evaluating Scaffolding-Oriented Multi-Agent Large Language Model System for Clinical Interview Training
Clinical education must prepare medical students to conduct safe and coherent patient interviews under conditions of uncertainty. Traditional standardized patient (SP) training is resource-intensive and difficult to scale. We developed a scaffolding-oriented multi-agent Large Language Model (LLM) AI
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