MedAidDialog: 一个多语言多轮医疗对话数据集用于可及性医疗
MedAidDialog: A Multilingual Multi-Turn Medical Dialogue Dataset for Accessible Healthcare
AI总结：
本文提出MedAidDialog数据集，用于模拟真实医患对话，通过生成合成对话扩展MDDial数据集，并开发MedAidLM模型以实现多轮对话和诊断推荐。
摘要：
对话式人工智能有潜力帮助用户进行初步医疗咨询，特别是在医疗专业人员难以获取的环境中。然而，许多现有医疗对话系统仅限于单轮问答或依赖模板数据集，限制了对话真实性和多语言适用性。本文介绍MedAidDialog，一个多语言多轮医疗对话数据集，旨在模拟真实的医患咨询。该数据集通过使用大型语言模型生成合成对话并扩展为覆盖七种语言的平行多语言数据集。基于此数据集，我们开发了MedAidLM，一个通过参数高效微调小型量化语言模型训练的对话医疗模型，无需高端计算基础设施即可部署。我们的框架还集成了可选的患者预上下文信息（如年龄、性别、过敏反应）以个性化咨询过程。实验结果表明，所提系统可通过多轮对话有效进行症状采集并生成诊断建议。我们进一步进行医学专家评估以评估生成咨询的合理性与连贯性。
英文摘要：
Conversational artificial intelligence has the potential to assist users in preliminary medical consultations, particularly in settings where access to healthcare professionals is limited. However, many existing medical dialogue systems operate in a single-turn question--answering paradigm or rely on template-based datasets, limiting conversational realism and multilingual applicability. In this work, we introduce MedAidDialog, a multilingual multi-turn medical dialogue dataset designed to simulate realistic physician--patient consultations. The dataset extends the MDDial corpus by generating synthetic consultations using large language models and further expands them into a parallel multilingual corpus covering seven languages: English, Hindi, Telugu, Tamil, Bengali, Marathi, and Arabic. Building on this dataset, we develop MedAidLM, a conversational medical model trained using parameter-efficient fine-tuning on quantized small language models, enabling deployment without high-end computational infrastructure. Our framework additionally incorporates optional patient pre-context information (e.g., age, gender, allergies) to personalize the consultation process. Experimental results demonstrate that the proposed system can effectively perform symptom elicitation through multi-turn dialogue and generate diagnostic recommendations. We further conduct medical expert evaluation to assess the plausibility and coherence of the generated consultations.
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。
