Диагностика глаукомы на современном этапе

Abstract

Thus far, practicing physicians perform glaucoma screening based on Graefe’s triad of symptoms. Considering the predicted increase in glaucoma incidence and the current trend in diagnosis verification at the time when patients already demonstrate significant changes in visual function, the issue on the need to revise these "markers" is raised. Summarizing the available modern diagnostic capabilities for glaucoma screening, it is fair to say that nowadays none of the diagnostic methods can "work alone". Only monitoring of glaucoma patients will help to determine accurately the presence or absence of glaucoma changes. Thus, the current standard for glaucoma detection includes several diagnostic methods. To receive reliable data on the disease prevalence, its diagnosis should be established in a timely manner. However, there are still difficulties faced in diagnosing glaucoma. This problem can be solved through the improvement of the available diagnostic tools and/or the introduction of novel methods of patient assessment. The advent of artificial intelligence (AI) technology, capable of learning and conducting in-depth analysis, has enabled the development of this approach. At the same time, the question of optimizing its application for practical medicine remains open. Keywords: primary open-angle glaucoma, glaucoma screening, glaucoma diagnosing, neural networks. For citation: Movsisyan A.B., Kuroyedov A.V. Making a diagnosis of glaucoma at the present time. Russian Journal of Clinical Ophthalmology. 2023;23(1):47–53 (in Russ.). DOI: 10.32364/2311-7729-2023-23-1-47-53.