Research on the Real-World Community Application of Large Language Models
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- This is an observational study: the protocol does not assign a study treatment.
- Who it may be relevant to
- Registry conditions: Ophthalmic Diseases (Specific Types Not Restricted). Basic parameters: No limits · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Center list to be confirmed — check the primary protocol.
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Unsure about the terms? Read our patient guide →
Overview
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.
Primary outcome measures
- Metrics for Evaluating Referral Accuracy of Large Language Models: Sensitivity, Specificity, Accuracy, Positive Predictive Value, Negative Predictive Value. [Time frame: through study completion, up to 1 year.]
Eligibility criteria
Inclusion criteria
- Participants of any age and gender
- Belonging to one of the following ophthalmic categories: Patients requiring specialist referral；Patients manageable at community level；Individuals without ocular pathology
- Voluntary participation with written informed consent
Exclusion criteria
- Investigator-determined clinical contraindications
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Observational model
- Other
Study locations
Center list to be confirmed — check the primary protocol.
Identifiers
NCT: NCT06966882 · 2025KYPJ020