UNAM Uses AI to Detect Diabetic Retinopathy in Mexican Patients

The National Autonomous University of Mexico is developing an artificial intelligence system to identify diabetic retinopathy early in Mexican patients using clinical imaging. The project trains algorithms on local databases to analyze retinal photographs and classify the severity of retinal damage.

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• UNAM develops an AI system to identify diabetic retinopathy in Mexican patients based on clinical images.

The National Autonomous University of Mexico is advancing an artificial intelligence model aimed at early detection of diabetic retinopathy. The project uses algorithms trained on local databases to analyze retinal photographs and classify the degree of retinal damage.

This tool seeks to reduce diagnostic time in medical units facing high demand and shortages of specialized staff. The development focuses on adapting to the demographic and epidemiological characteristics of the Mexican population, where type 2 diabetes represents a significant risk factor for visual complications.

The system prioritizes accessibility through interfaces that can integrate with imaging equipment already in place at public-sector clinics. UNAM researchers emphasize that model validation occurs through controlled clinical studies to measure sensitivity and specificity in real-world care settings.

The effort is part of broader university initiatives to apply machine learning technologies to public health problems with high prevalence across the country.

Sources:

Nobiu UNAM

https://nobiu.unam.mx/?page_id=2713

This article was written with artificial intelligence assistance from verified sources and reviewed by a human editor before publication.