Zhiqi Gao, Huarui Luo, Guo Zhu, Bingquan Zhang, Dongyijie Primo Pan, Yizhan Feng, Jiahuan Pei, Jie Li, Benyou Wang (2026) — Institution.
MedEasy multi-agent system simulates standardized patients with varying conditions for medical consultation training; outperforms script-based approaches in realism and adaptability.
Synthesis
MedEasy: Designing AI Standardized Patients for Clinical Consultation Training investigates medeasy multi-agent system simulates standardized patients with varying conditions for medical consultation training; outperforms script-based approaches in realism and adaptability. This work connects to existing research on accessible-learning by demonstrating that Abstract:AI standardized patients are becoming a setting for professional training in clinical consultation. This paper presents MedEasy, a multi-agent system that organizes virtual-patient practice through patient dialogue, clinical actions, decision submission, documentation, and feedback. We firs....
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Citation
APA: Zhiqi Gao, Huarui Luo, Guo Zhu, Bingquan Zhang, Dongyijie Primo Pan, Yizhan Feng, Jiahuan Pei, Jie Li, Benyou Wang (2026). MedEasy: Designing AI Standardized Patients for Clinical Consultation Training. arXiv:2606.17512.