About this trial
This is a retrospective, multicenter, observational study designed to develop and validate an artificial intelligence (AI) system capable of detecting and classifying major ophthalmic diseases (glaucoma, cataract, diabetic retinopathy, and other retinal pathologies) in the Costa Rican population. The study will use approximately 15,000 existing medical images from digital archives of two ophthalmic centers in Costa Rica, without active participant recruitment or capture of new images.
The primary motivation is that AI systems developed in other countries (primarily Asian, European, or North American populations) do not necessarily perform with the same accuracy when applied to Latin American populations. This study seeks to establish a precedent for the importance of locally validating any medical AI technology before clinical implementation.
Eligibility criteria
Qualifiers
Image corresponds to patient ≥18 years of age at time of capture
Image modality is one of: fundus photography, posterior segment OCT, anterior segment photography, automated perimetry, or video-OCT
Image quality sufficient for diagnostic interpretation (adequate resolution, focus, illumination, complete visualization of anatomical area of interest, no major artifacts)
Minimum clinical data available (age or age group, sex, and diagnosis or clinical indication)
Disqualifiers
Images from eyes with recent intraocular surgery (<3 months)
Images from eyes with severe ocular trauma distorting anatomy
Images from patients with rare or unique ocular pathologies not allowing generalization
Images post-recent laser treatment where acute changes may confuse analysis
Trial design
Treatments tested in this trial
- No interventions