HealthDial：一款面向医疗虚拟智能体的无代码 LLM 辅助对话创作工具
HealthDial: A No-Code LLM-Assisted Dialogue Authoring Tool for Healthcare Virtual Agents
AI总结：
本文提出 HealthDial，一种利用 LLM 从健康教育材料生成可编辑有限状态机对话的无代码工具，并通过癌症筛查创作任务验证其可行性与可用性。
摘要：
我们推出 HealthDial，这是一款对话创作工具，可帮助医疗服务提供者和教育工作者创建虚拟智能体，在多次对话中向患者提供健康教育与咨询。HealthDial 利用大语言模型（LLM），以基于文本的患者健康教育材料为输入，自动创建初始的基于会话的计划以及每次会话的对话。所创作的对话以有限状态机的形式输出，用于虚拟智能体交付，以便所有内容都能得到验证，并且不会因 LLM 幻觉而提供不安全的建议。作者可以在无代码用户界面中编辑 LLM 起草的对话结构和语言，以确保有效性并优化清晰度与影响力。我们与咨询人员和学生开展了一项可行性和可用性研究，通过癌症筛查教育的创作任务来测试我们的方法。参与者使用 HealthDial，随后通过与一个交付该对话的 3D 动画虚拟智能体交互，测试他们生成的对话。通过参与者对任务体验和最终对话的评估，我们表明，HealthDial 为咨询人员确保完整覆盖其健康教育材料，同时创建患者可理解且可执行的虚拟智能体对话，提供了富有前景的第一步。
英文摘要：
We introduce HealthDial, a dialogue authoring tool that helps healthcare providers and educators create virtual agents that deliver health education and counseling to patients over multiple conversations. HealthDial leverages large language models (LLMs) to automatically create an initial session-based plan and conversations for each session using text-based patient health education materials as input. Authored dialogue is output in the form of finite state machines for virtual agent delivery so that all content can be validated and no unsafe advice is provided resulting from LLM hallucinations. LLM-drafted dialogue structure and language can be edited by the author in a no-code user interface to ensure validity and optimize clarity and impact. We conducted a feasibility and usability study with counselors and students to test our approach with an authoring task for cancer screening education. Participants used HealthDial and then tested their resulting dialogue by interacting with a 3D-animated virtual agent delivering the dialogue. Through participants' evaluations of the task experience and final dialogues, we show that HealthDial provides a promising first step for counselors to ensure full coverage of their health education materials, while creating understandable and actionable virtual agent dialogue with patients.
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。
