The intelligent image models lack an understanding of diagnostic and treatment logic, and have not considered textual information such as symptoms and signs. Large language models like ChatGPT, can learn medical knowledge, understand, and generate human natural language, offering new technologies for medical knowledge-based intelligent question answering and the creation of smart medical documents. Therefore, our team plan to verify large language models' feasibility and effectiveness in ophthalmology clinics for medical history collection and examination recommendations during consultations, comparing its performance with traditional methods.
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See this in plain English?
AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Bring these to your next appointment. They're a starting point for a shared conversation — not a sign you qualify or a recommendation to enrol.
Generated to help you prepare — always confirm anything about your own eligibility and care with the study team and your doctor.
The trial coordinator is the person who runs the study day to day. These cover the practical side — logistics, costs, and what taking part would actually mean for your life. The study team confirms whether you meet the criteria; these are questions to ask, not a sign you qualify.
A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.
Medical History Collection Scoring
Timeframe: through study completion, up to 1 week.