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Synthetic Patient–Physician Conversations Simulated by Large Language Models: A Multi-Dimensional Evaluation
4
Zitationen
11
Autoren
2025
Jahr
Abstract
Leading LLMs can generate medically accurate, emotionally appropriate synthetic dialogues suitable for educational and research use. Despite high performance, demographic homogeneity in generated patients highlights the need for improved diversity and bias mitigation in model outputs. These findings support the cautious, context-aware integration of LLM-generated dialogues into medical training, simulation, and research.
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