Clinical Research Directory

Research on a New Intelligent Mobile Screening and Diagnosis Pattern for Ocular Diseases

The global distribution of primary ophthalmic medical resources is uneven, and the traditional eye disease screening model has problems such as low efficiency, high cost and limited coverage. With the development of artificial intelligence and other technologies, it provides technical support for the construction of intelligent mobile screening model for eye diseases. The investigator's team has developed the 5G intelligent ophthalmic vehicle and served tens of thousands of people in 108 cities nationwide, initially verifying the feasibility of the new intelligent mobile screening model. However, the application effect, acceptance and influencing factors of this model in different regions are not clear, and there is a lack of economic benefit analysis based on real-world data. In this study, the investigators will conduct a cross-sectional study of large-scale population screening for blinding eye diseases in grassroots areas through the smart mobile screening model, focusing on the screening effectiveness and cost-effectiveness of the smart mobile screening model, integrating real-world multimodal eye health data, developing multiple smart screening analysis models, and exploring its adaptability and direction of improvement in grassroots areas.

Research on the Real-World Community Application of Large Language Models

There is an imbalance between the supply and demand of eye care services, especially in local communities and remote areas. To address this, it's important to use new intelligent technologies to expand the reach of eye disease screening and treatment. Large language models (LLMs) are a type of deep learning technology that can learn from large amounts of text and generate human-like language to help with medical tasks such as diagnosing diseases and answering health-related questions. The investigator's team has previously developed a localized LLM capable of answering ophthalmology-related medical questions. Building on this, this study plans to use a screening-based trial design to explore how accurately the LLM can make referral decisions for eye diseases, diagnose conditions, recommend appropriate tests, and receive user feedback in real-world community settings. The goal is to improve the ability to screen for eye diseases in grassroots and regional areas.