Multimodal Deep Learning Model for Multi-task Diagnosis and Triage Suggestions of Ophthalmic Diseases

Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorGuangdong Provincial People's Hospital

About this trial

Accurate and comprehensive interpretation of anterior segment diseases from slit-lamp and smartphone photographs remains a clinical challenge due to the limited specificity and structure of existing Artificial Intelligence tools. The purpose of this international, multicenter clinical trial is to developed and validated an agent-based framework that integrates vision-language models and large language models to enhance the diagnostic workflow of anterior segment diseases.

Eligibility criteria

Qualifiers

Informed consent obtained;

Participants should be sufficiently able to read, write, and understand Chinese or English;

For normal participants: individuals should have no concerns related to their eyes.

For participants with eye-related chief complaints: individuals should have specific concerns or issues related to their eyes.

Disqualifiers

Incomplete clinical data to support final diagnosis;

Patients who, in the opinion of the attending physician or clinical study staff, are too medically unstable to participate in the study safely.

Trial design

Treatments tested in this trial

  • Multimodal Vision-language Model Diagnosis

Treatment groups

2,000 Participants
are divided into 2 treatment groups