Detection and Classification of Diabetic Retinopathy From Posterior Pole Images With A Deep Learning Model

The duration of diabetes is directly related to eye complications. Diabetic retinopathy affects 80 percent of those who have had diabetes for 20 years or more. At least 90% of new cases can be reduced with proper treatment and monitoring of the eyes. The longer a person has diabetes, the more likely it is to develop diabetic retinopathy. Each year in the United States, diabetic retinopathy accounts for 12% of all new cases of blindness. It is also the leading cause of blindness in people between the ages of 20 and 64. The most important complication of diabetes leading to vision loss is diabetic retinopathy. Depending on this, macular edema, bleeding into the retina and vitreous,neovascular glaucoma can cause blindness.

Diabetic retinopathy (DR) is a leading cause of vision-loss globally. Of an estimated 285 million people with diabetes mellitus worldwide, approximately one third have signs of DR and of these, a further one third of DR is vision-threatening DR, including diabetic macular edema (DME). Diabetic retinopathy is a retinal disease that can often be stopped with early diagnosis, but if neglected, it can lead to severe vision loss, including permanent blindness. Diabetes has high morbidity and there are millions of people who should be screened for diabetic retinopathy (DR). Annual eye screening is recommended for all diabetic patients since vision loss can be prevented if DR is diagnosed in its early stages. Currently, the number of clinical personnel trained for DR screening is less than that needed to screen a growing diabetic population. Therefore, the automatic DR screening system will be able to screen more diabetic patients and diagnose them early.

EyeCheckup is an automated retinal screening device designed automatically analyze color fundus photographs of diabetic patients to identify patients with referable or vision threatening DR. This study is designed to assess the safety and efficacy of EyeCheckup.

The study is a single center study to determine the sensitivity and specificity of EyeCheckup to diabetic retinopathy. EyeCheckup is an automated software device that is designed to analyze ocular fundus digital color photographs taken in frontline primary care settings in order to quickly screen for diabetic retinopathy (DR).