Type 2 diabetes patients in China face many significant challenges in patient-provider communication and self management In light of this, this work designed,implemented,and evaluated an AI-driven, personalized, multi-functional mobile app system named T2MD Health. The appintegrates real-time patient- provider conversation transcription,medical terminology interpretation, daily health tracking, and adata-driven feedback loop. We conducted qualitative interviewswith 40 participants to study key user needs before systemdevelopment and a mixed- method controlled experiment with 60participants after to evaluate the effectiveness and usability ofthe app. Evaluation results showed that the app was effective inimproving patient-provider communication efficiency, patientunderstanding and knowledge retention,and patient selfmanagement, Patient feedback also revealed that the app has thepotential to address the urban-rural gap in the access to medica!consultation services to some extent, Findings ofthis study couldinform future studies that seek to utilize mobile apps andartificial intelligence to support patients with chronic diseases.

翻译：中国2型糖尿病患者在医患沟通和自我管理方面面临诸多重大挑战。为此，本研究设计、实现并评估了一款名为T2MD Health的AI驱动、个性化、多功能移动应用系统。该应用整合了实时医患对话转录、医学术语解释、日常健康追踪以及数据驱动的反馈循环机制。在系统开发前，我们通过对40名参与者的定性访谈研究了核心用户需求；系统开发后，采用混合方法对60名参与者进行了对照实验，以评估应用的有效性和可用性。评估结果表明，该应用能有效提升医患沟通效率、患者理解与知识留存能力以及患者自我管理水平。患者反馈同时显示，该应用在一定程度上具备缓解城乡医疗咨询服务可及性差距的潜力。本研究结果可为未来利用移动应用和人工智能支持慢性病患者的相关研究提供参考。