NCT07497815Not yet recruiting
Artificial Intelligence-assisted Diagnosis in Ophthalmology
Development and Validation of an Artificial Intelligence-assisted Diagnostic System for Ophthalmic Pathologies
Source: ClinicalTrials.gov · Last updated 1 Apr 2026
Brief summary (registry, in English)
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.
- Status (registry)
- Not yet recruiting
- Study type
- Observational
- Enrollment
- 15000 (estimated)
- First submitted
- 23 Mar 2026
- Start date
- 1 May 2026
- Primary completion date
- 1 May 2028
- Lead sponsor
- Marisse Masis-Solano
- Diseases
- Glaucoma, Macular degeneration, Diabetic eye disease
- NCT number
- NCT07497815
What you commit to
- Study type: Observational
- Planned participants: 15000
- From 1 May 2026 to the primary completion date, 1 May 2028
- 2 sites in 1 country
- Visits and tests: ask the trial team, the registry does not list them
Built from the registry fields of ClinicalTrials.gov. It describes the study, not your situation.
Who cannot take part
Copied verbatim from ClinicalTrials.gov and grouped by topic. Only the trial team decides who can take part.
Prior treatment
- Images from eyes with recent intraocular surgery (\<3 months)
Age
- 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)
Other
- CLINICAL:
- 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
Who the study is looking for
- 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)
Age in the registry: 18 years to - · Sex: All · Accepts healthy volunteers
Sites (2)
Sites in registry order. Pick your city on the disease page to sort them by distance.
| Site | City | Country | Site status |
|---|---|---|---|
| Centro Ocular Coordinator of this site? Confirm its status | Heredia | Costa Rica | Unknown status |
| Asociados de Mácula y Vítreo de Costa Rica Coordinator of this site? Confirm its status | San José | Costa Rica | Unknown status |
This page is information, not medical advice. Discuss any trial with your doctor.