ARTIFICIAL INTELLIGENCE IN OPHTHALMOLOGY

In recent years, artificial intelligence (AI) has become increasingly important in ophthalmology, opening up new opportunities for the early diagnosis, monitoring, and prognosis of ophthalmic diseases. This article examines modern methods for applying AI, including machine learning and deep neural networks, to the analysis of ophthalmic images, such as fundus photographs, optical coherence tomography, and ultrasound data. Particular attention is paid to the use of AI for the detection of glaucoma, diabetic retinopathy, age-related macular degeneration, and other common eye diseases. The advantages and limitations of implementing intelligent systems in clinical practice, as well as issues of accuracy, interpretability, and the integration of AI solutions into existing diagnostic processes, are also analyzed . The results of the study confirm the high potential of artificial intelligence as an effective tool for supporting medical decision-making and improving the quality of ophthalmic care.