PatientSim：一种用于生成真实医患交互的角色驱动型模拟器
PatientSim: A Persona-Driven Simulator for Realistic Doctor-Patient Interactions
AI总结：
针对现有患者模拟器难以覆盖临床多样患者角色的问题，研究提出基于医学知识的PatientSim模拟器，结合真实临床数据与四维度角色生成多样交互场景，验证了其作为医疗对话系统测试与教育工具的价值。
摘要：
医患问诊需要针对不同患者角色定制的多轮、上下文感知的沟通。在此类场景中训练或评估医生大语言模型（LLM）需要真实的患者交互系统。然而，现有模拟器往往无法反映临床实践中存在的全部角色类型。为解决这一问题，我们提出PatientSim——一款以医学专业知识为基础、可为临床场景生成真实多样患者角色的患者模拟器。PatientSim的运行基于两大要素：1）源自MIMIC-ED和MIMIC-IV数据集真实数据的临床档案，包括症状和病史；2）从性格、语言能力、病史回忆程度、认知混乱程度四个维度定义的患者角色，共形成37种独特组合。我们对8款LLM的事实准确性和角色一致性进行了评估，其中表现最佳的开源模型Llama 3.3 70B经四名临床医生验证，确认了本框架的稳健性。作为一款开源可定制平台，PatientSim提供了可复现、可扩展的解决方案，可根据特定训练需求定制。它还具备隐私合规的环境，是评估面向不同患者表现的医疗对话系统的可靠测试平台，也有望成为医疗保健领域的教育工具。代码可在https://github.com/dek924/PatientSim获取。
英文摘要：
Doctor-patient consultations require multi-turn, context-aware communication tailored to diverse patient personas. Training or evaluating doctor LLMs in such settings requires realistic patient interaction systems. However, existing simulators often fail to reflect the full range of personas seen in clinical practice. To address this, we introduce PatientSim, a patient simulator that generates realistic and diverse patient personas for clinical scenarios, grounded in medical expertise. PatientSim operates using: 1) clinical profiles, including symptoms and medical history, derived from real-world data in the MIMIC-ED and MIMIC-IV datasets, and 2) personas defined by four axes: personality, language proficiency, medical history recall level, and cognitive confusion level, resulting in 37 unique combinations. We evaluate eight LLMs for factual accuracy and persona consistency. The top-performing open-source model, Llama 3.3 70B, is validated by four clinicians to confirm the robustness of our framework. As an open-source, customizable platform, PatientSim provides a reproducible and scalable solution that can be customized for specific training needs. Offering a privacy-compliant environment, it serves as a robust testbed for evaluating medical dialogue systems across diverse patient presentations and shows promise as an educational tool for healthcare. The code is available at https://github.com/dek924/PatientSim.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
