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Artificial Intelligence-Assisted Lesion-Based Urgent Referral Triage of Ultra-Widefield Retinal Images: A Multi-Reader Multi-Case Randomized Reader Study
Sponsor: Xiamen Ophthalmology Center Affiliated to Xiamen University
Summary
his study evaluates the clinical utility of an artificial intelligence (AI)-assisted lesion-based urgent referral triage system for ultra-widefield (UWF) retinal images. Unlike disease-classification systems, the AI system identifies predefined vision-threatening retinal findings and generates lesion-level urgent referral recommendations. Participating ophthalmologists will evaluate UWF retinal images under randomized AI-assisted and unassisted conditions. The primary objective is to determine whether lesion-based AI assistance improves urgent referral triage performance compared with unaided image interpretation.
Official title: Clinical Utility of an Artificial Intelligence-Assisted Lesion-Based Urgent Referral Triage System for Ultra-Widefield Retinal Images: A Prospective Multi-Reader Multi-Case Randomized Reader Study
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
INTERVENTIONAL
Enrollment
8
Start Date
2026-06-15
Completion Date
2026-06-30
Last Updated
2026-06-11
Healthy Volunteers
Yes
Conditions
Interventions
AI-Assisted UWF Lesion-Based Triage System
Readers interpret UWF retinal images with lesion-level AI findings and urgent referral recommendations.
Unassisted Interpretation
Readers interpret UWF retinal images without AI assistance.