aceWhy aren't we using AI in eye clinics? A systematic review of barriers and solutions in AI-based fundus image diagnostics for ocular diseases
Artificial intelligence (AI) has shown remarkable accuracy in the diagnosis of common ocular diseases such as diabetic retinopathy (DR), glaucoma, retinopathy of prematurity (ROP), and age-related macular degeneration (AMD), often matching or even outperforming expert clinicians. Despite these advancements, AI adoption in clinical settings remains limited due to key barriers. This systematic review evaluates 34 studies (2018-2025) highlighting AI's diagnostic performance (often >90% accuracy) while pointing out…
Despite high accuracy, AI fundus diagnostics saw limited clinical adoption due to poor generalizability and disjointed workflow integration.
Evidence
- Peer-reviewedInternational Journal of Ophthalmology2026-09-18
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Truvace Impact Record TRV-2026-1127, v1: “Why aren't we using AI in eye clinics? A systematic review of barriers and solutions in AI-based fundus image diagnostics for ocular diseases.” Truvace, 2026-09-18. /record/TRV-2026-1127 (accessed at citation time). sha256 a88ccff32e491416…
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