Assessment of Hypertensive Retinopathy Using Neural Network "RetinAIcheck"

The current study is aimed at estimating the diagnostic effectiveness of a developed neural network "RetinAIcheck" in grading the severity of hypertensive retinopathy in patients of the Russian population. The training data set was obtained from an open source and relabeled by seven independent retina specialists, the sample size was 30,000 fundus photographs. The test sample included 755 patients (1374 eyes). Among the 1.374 eyes, 94 were without HR (class 0), 330 had class 1, 660 had class 2, 280 had class 3, and 10 had class 4 HR.The reference standard was the result of independent grading of HR stage by two ophthalmologists, controversial clinical cases were evaluated with the involvement of a third ophthalmologist.

Inclusion Criteria: \- Patients with and without a diagnosis of arterial hypertension, based on medical records Exclusion Criteria: * anophthalmia, * optic nerve atrophy, * eyeball injuries, * age-related macular degeneration, * central serous chorioretinopathy, * central serous chorioretinitis, * clouding of the optical media of the eye, which affects the quality of the image.