Traditional diagnosis of chronic diseases involves in-person consultations
with physicians to identify the disease. However, there is a lack of research
focused on predicting and developing application systems using clinical notes
and blood test values. We collected five years of Electronic Health Records
(EHRs) from Taiwan's hospital database between 2017 and 2021 as an AI database.
Furthermore, we developed an EHR-based chronic disease prediction platform
utilizing Large Language Multimodal Models (LLMMs), successfully integrating
with frontend web and mobile applications for prediction. This prediction
platform can also connect to the hospital's backend database, providing
physicians with real-time risk assessment diagnostics. The demonstration link
can be found at this https URL

利用电子健康记录和大型语言多模型，我们开发了基于电子健康记录的慢性病预测平台，该平台可以与前端网络和移动应用程序成功集成，以实现实时风险评估诊断。