ABSTRACT Objective: To assess the diagnostic accuracy of a deep learning tool for cataract detection using retinal images from the Ocular Disease Intelligent Recognition (ODIR) public dataset. Methods: The study was conducted using a publicly available dataset, with a web-based Artificial Intelligence tool. This was an observational, cross-sectional study. A total of 230 fundus images were selected from the ODIR dataset, equally divided between 115 cataract cases and 115 non-cataract cases. The images were processed using the Gobvision Artificial Intelligence […]

ABSTRACT Introduction: To obtain fundoscopy images through portable and low-cost equipment using artificial intelligence to assess the presence of DR. Methods: Fundus images of diabetic patients’ eyes were obtained by using a smartphone coupled to a device with a 20D lens. By using artificial intelligence (AI), the presence of DR was classified by a binary algorithm. Results: 97 ocular fundoscopy images were evaluated (45 normal and 52 with DR). Through AI diagnostic accuracy around was 70% to 100% in the […]

ABSTRACT Currently the “pandemic” of diabetes mellitus is noted. The incidence and prevalence of diabetes and diabetic retinopathy, the most common microvascular complications of diabetes, are exponentially growing due to increased life expectancy in many parts of the world. The increasing number of people suffering from diabetic retinopathy not only highlights medical issues, but also an economic burden, representing a medical and social challenge. It is extremely important to identify a disease as soon as possible and successfully treat it. […]