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TruaceTracing the truth around AIWednesday, August 5, 2026
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TRV-2026-0564Certified recordPeer-reviewed

Ultra-widefield color fundus images and artificial intelligence for diagnosis of diabetic retinopathy: A systematic review and meta-analysis

Ultra-widefield (UWF) fundus cameras capture a larger retinal area without pupil dilation. We summarized evidence and diagnostic performance of artificial intelligence (AI)-driven diabetic retinopathy (DR) assessments using UWF images (UWFIs). We searched PubMed, Scopus, the Cochrane Library, and Web of Science to February 9, 2025, for studies evaluating DR using UWFIs and AI analyses. We followed the PRISMA guidelines and assessed study quality using the Joanna Briggs Institute Critical Appraisal Checklist for…

Health · The Trace — both readings · certified 2026-07-25 · v1 · article view · machine-readable

Current reading — gain

AI-driven diabetic retinopathy screening using ultra-widefield fundus images achieved a summary sensitivity of 85.0% and AUC of 0.870 in meta-analysis.

Current reading — problem

AI-driven diabetic retinopathy screening using ultra-widefield fundus images showed limited specificity of 72.5% in meta-analysis.

What this doesn’t fix

Findings are limited by small evidence base and lack of diverse external validation across platforms.

Evidence

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Truvace Impact Record TRV-2026-0564, v1: “Ultra-widefield color fundus images and artificial intelligence for diagnosis of diabetic retinopathy: A systematic review and meta-analysis.” Truvace, 2026-07-25. /record/TRV-2026-0564 (accessed at citation time). sha256 957677c8385dbd93…

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