Artificial Intelligence in Eye Disease: A Systematic Review of Screening, Diagnosis, Prognosis, Treatment-Response Prediction, and Clinical Decision Support
Background/Objectives: Artificial intelligence (AI) is expanding eye care beyond image-based detection toward prognosis, treatment-response prediction, monitoring, triage, and clinician-facing decision support. We evaluated AI across eye-disease screening, diagnosis, prognosis, treatment response, and decision support, emphasizing validation, explainability, and clinical readiness. Methods: This PROSPERO-registered review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 20…
Eye-disease AI is not yet clinically ready: independent validation is incomplete, direct clinician comparators are scarce, and safety, workflow and patient-outcome evidence is sparse.
Heterogeneity precluded meta-analysis, and the authors report incomplete independent validation, few direct comparators and sparse evaluation of safety, workflow effects and patient outcomes.
Evidence
- Peer-reviewedJournal of Clinical Medicine2026-10-14
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Truvace Impact Record TRV-2026-1490, v1: “Artificial Intelligence in Eye Disease: A Systematic Review of Screening, Diagnosis, Prognosis, Treatment-Response Prediction, and Clinical Decision Support.” Truvace, 2026-10-15. /record/TRV-2026-1490 (accessed at citation time). sha256 9e37524a4057909f…
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