Artificial intelligence and neural networks in the diagnosis of glaucoma

Abstract

Early diagnosis of glaucoma and objective analysis of data obtained from instrumental study methods is one of the most important problems in ophthalmology. Modern state of technological development allows implementing artificial intelligence and neural networks in the diagnosis and treatment of glaucoma. Special software helps perform perimetry using portable devices, which reduces the workload for medical facilities and lowers the costs of the procedure. Mathematical models allow evaluating the risk of glaucoma progression based on instrumental findings. Artificial intelligence allows assessing the results of Goldman and Maklakov tonometry and determining the state of disease progression by analyzing a series of 2D and 3D data (scan images of optic nerve head, static perimetry etc.) separately, as well as in complex analysis of data from various devices.