本研究提出了一个基于大语言模型的创新性多智能体协作平台——5A MedAgent系统，通过5个专业智能体［询问智能体（Ask Agent）、评估智能体（Assessment Agent）、建议智能体（Advice Agent）、安排智能体（Arrangement Agent）以及辅助智能体（Assistance Agent）］的协同运作，实现患者教育的全流程智能管理，为复杂疾病诊疗提供了更精准的个性化方案和专业解释，推动了智能医疗教育的发展。

This study presents an intelligent system for patient education based on large language model (LLMs) and multi agent collaboration, achieving end-to-end process management through five specialized agents (Ask Agent, Assessment Agen, Advice Agent, Arrangement Agent, and Assistance Agent). The system not only improves treatment efficiency, but also provides more precise personalized treatment plans for complex cases, demonstrating significant value in enhancing patient education quality.