用AI助手帮癌症患者准备诊疗问诊，提升沟通效率。
Patient-Centered RAG for Oncology Visit Aid Following the Ottawa Decision Guide
- 将决策指南转化为动态RAG流程，引导患者补知识、明需求。
- 用户测试显示系统易用性高，生成内容相关性强且临床可信度达6.82。
- 适合关注医患沟通质量的临床医生与医疗AI研发者。
在癌症治疗中，有效沟通至关重要，但患者常难以为复杂诊疗会话做好准备。本文提出一种以患者为中心的交互式检索增强生成系统，协助患者从无知状态转变为就诊准备就绪。系统将奥特拉个人决策指南改造为动态的检索增强生成工作流，帮助用户填补知识空白、厘清个人价值观，并生成针对即将到来诊疗的有用问题。以局部前列腺癌为例，我们对患者和临床专家进行了用户研究。结果表明，系统具有高可用性（UMUX均值=6.0/7）、生成内容强相关性（均值=6.7/7）、极少需要修改，且临床忠实度高（均值=6.82/7）。本研究展示了将患者中心设计与语言模型结合，在肿瘤科临床准备中的巨大潜力。
原文摘要 · Abstract (English)
Effective communication is essential in cancer care, yet patients often face challenges in preparing for complex medical visits. We present an interactive, Retrieval-augmented Generation-assisted system that helps patients progress from uninformed to visit-ready. Our system adapts the Ottawa Personal Decision Guide into a dynamic retrieval-augmented generation workflow, helping users bridge knowledge gaps, clarify personal values and generate useful questions for their upcoming visits. Focusing on localized prostate cancer, we conduct a user study with patients and a clinical expert. Results show high system usability (UMUX Mean = 6.0 out of 7), strong relevance of generated content (Mean = 6.7 out of 7), minimal need for edits, and high clinical faithfulness (Mean = 6.82 out of 7). This work demonstrates the potential of combining patient-centered design with language models to enhance clinical preparation in oncology care.
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