Artificial Intelligence-Assisted Lesion-Based Urgent Referral Triage of Ultra-Widefield Retinal Images

Conditions: Vision-Threatening Retinal Lesions, Urgent Referral Retinal Findings, Retinal Detachment, Pre-retinal Hemorrhage, Subretinal Hemorrhage, Retinal Neovascularization

Sex: All

Ages: 18 Years – N/A

Healthy volunteers: Yes

Phase: NA

Enrollment: 8

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.

Eligibility Criteria

Inclusion Criteria: * Licensed ophthalmologists * Willing to participate as readers * Completion of study training Exclusion Criteria: * Retinal specialists involved in establishing gold-standard labels * Prior access to gold-standard labels * Incomplete study participation

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View on ClinicalTrials.gov

Source: ClinicalTrials.gov (NCT07643129). StuddyBuddy aggregates publicly available trial information.