Artificial Intelligence-assisted Diagnosis in Ophthalmology

Inclusion Criteria: * 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) * Image captured during routine clinical care (not specifically for research) * No patient objection to use of medical data for research (when applicable per center policy) Exclusion Criteria: CLINICAL: * 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 TECHNICAL: * Severely degraded image quality (extreme blur, severe under/overexposure, major artifacts preventing interpretation) * Duplicate images of same eye on same date * Images with missing or clearly erroneous metadata * Images in non-standard or corrupted formats that cannot be processed Sex/Gender: All Minimum Age: 18 Years Maximum Age: No limit Accepts Healthy Volunteers: Yes (images of healthy eyes without pathology are included as controls)