N I Kurysheva, A L Pomerantsev, O Ye Rodionova, G A Sharova
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引用次数: 0
Abstract
This article reviews literature on the use of artificial intelligence (AI) methods for the diagnosis and treatment of primary angle-closure disease (PACD). The review describes how AI techniques enhance the efficiency of population screening for anterior chamber angle closure, presents technologies utilizing deep learning, including neural networks, for the analysis of large datasets obtained through anterior segment imaging methods, such as anterior segment optical coherence tomography (AS-OCT), digital gonioscopy, and ultrasound biomicroscopy, and discusses methods for treating PACD with the help of AI. Integration of deep learning and imaging techniques represents a crucial step in optimizing the diagnosis and treatment of PACD, reducing the burden on the healthcare system.
期刊介绍：
The journal publishes materials on the diagnosis and treatment of eye diseases, hygiene of vision, prevention of ophthalmic affections, history of Russian ophthalmology, organization of ophthalmological aid to the population, as well as the problems of special equipment. Original scientific articles and surveys on urgent problems of theory and practice of Russian and foreign ophthalmology are published. The journal contains book reviews on ophthalmology, information on the activities of ophthalmologists" scientific societies, chronicle of congresses and conferences.The journal is intended for ophthalmologists and scientific workers dealing with clinical problems of diseases of the eye and physiology of vision.
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