Theoretical analysis of scientifically based applications of artificial intelligence in ophthalmology

Abstract

Background. The article is based on a meta-theoretical analysis of 39 studies on the use of artificial intelligence (AI) in ophthalmology published in peer-reviewed journals from 2019 to 2024, to determine the possibility of implementing their findings in Ukraine, in particular in the context of the Russian-Ukrainian war. Data are provided on the ability of AI to significantly improve the quality of screening, diagnosis, and treatment of diseases such as diabetic retinopathy, glaucoma, and age-related macular degeneration. The purpose was to investigate the possibilities of using AI to improve the diagnosis and treatment of ophthalmic diseases in the context of modern challenges, including military conflicts. Materials and methods. Artificial intelligence tools, including deep learning algorithms, large language models, and generative AI systems, demonstrate clinically valid diagnostic accuracy, particularly in neuro-ophthalmology, in patients with ocular injuries as a result of traumatic brain injury. The issue of robust data management and ethical guidelines is considered in the context of CONSORT-AI. Results. During prolonged Russian-Ukrainian war, appropriate AI-based telemedicine models can provide fast remote access to specialized care for wounded soldiers and civilians. Conclusions. AI is already having a significant impact on the ophthalmic care system, and its implementation depends on both technical validation and ongoing consistent ethical oversight.

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