Actively Recruiting
Multimodal Deep Learning Model for Multi-task Diagnosis and Triage Suggestions of Ophthalmic Diseases
Led by Guangdong Provincial People's Hospital · Updated on 2026-03-05
2000
Participants Needed
1
Research Sites
126 weeks
Total Duration
On this page
AI-Summary
What this Trial Is About
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.
CONDITIONS
Official Title
Multimodal Deep Learning Model for Multi-task Diagnosis and Triage Suggestions of Ophthalmic Diseases
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Provided informed consent
- Able to read, write, and understand Chinese or English
- For normal participants: No eye-related concerns
- For participants with eye complaints: Have specific eye-related concerns or issues
You will not qualify if you...
- Incomplete clinical data to support final diagnosis
- Medically unstable as judged by the attending physician or study staff
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Trial Site Locations
Total: 1 location
1
Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University
Guangzhou, Guangdong, China, 510280
Actively Recruiting
Research Team
H
Honghua Yu
CONTACT
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
2
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