通过支持AI的基于聊天机器人的症状诊断器进行自我诊断：用户体验和设计考虑
Self-Diagnosis through AI-enabled Chatbot-based Symptom Checkers: User Experiences and Design Considerations
摘要：
最近，人们对在医疗保健市场开发基于AI的聊天机器人的症状检查器（CSC）应用程序的兴趣越来越大。CSC应用程序为用户提供潜在的诊断，并使用类似人类的对话，基于人工智能（AI）技术帮助他们进行自我分类。尽管这些CSC应用程序很受欢迎，但很少有研究调查它们的功能和用户体验。为此，我们进行了功能审查，用户审查分析和访谈研究。我们发现，现有的CSC应用程序缺乏支持离线医疗访问的整个诊断过程的功能。我们还发现，用户认为当前CSC应用程序缺乏对全面病史、灵活症状输入、可理解问题以及多样化疾病和用户组的支持。基于这些结果，我们得出了CSC应用程序的未来功能和会话设计的影响。
英文摘要：
Recently, there has been a growing interest in developing AI-enabled chatbot-based symptom checker (CSC) apps in the healthcare market. CSC apps provide potential diagnoses for users and assist them with self-triaging based on Artificial Intelligence (AI) techniques using human-like conversations. Despite the popularity of such CSC apps, little research has been done to investigate their functionalities and user experiences. To do so, we conducted a feature review, a user review analysis, and an interview study. We found that the existing CSC apps lack the functions to support the whole diagnostic process of an offline medical visit. We also found that users perceive the current CSC apps to lack support for a comprehensive medical history, flexible symptom input, comprehensible questions, and diverse diseases and user groups. Based on these results, we derived implications for the future features and conversational design of CSC apps.
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。
