Kurysheva N I, Rodionova O Ye, Pomerantsev A L, Sharova G A
Medical Biological University of Innovations and Continuing Education of the Federal Biophysical Center named after A.I. Burnazyan, Moscow, Russia.
Ophthalmological Center of the Federal Medical-Biological Agency at the Federal Biophysical Center named after A.I. Burnazyan, Moscow, Russia.
Vestn Oftalmol. 2024;140(4):80-85. doi: 10.17116/oftalma202414004180.
The second part of the literature review on the application of artificial intelligence (AI) methods for screening, diagnosing, monitoring, and treating glaucoma provides information on how AI methods enhance the effectiveness of glaucoma monitoring and treatment, presents technologies that use machine learning, including neural networks, to predict disease progression and determine the need for anti-glaucoma surgery. The article also discusses the methods of personalized treatment based on projection machine learning methods and outlines the problems and prospects of using AI in solving tasks related to screening, diagnosing, and treating glaucoma.
关于人工智能（AI）方法在青光眼筛查、诊断、监测和治疗中的应用的文献综述的第二部分，提供了有关AI方法如何提高青光眼监测和治疗效果的信息，介绍了使用机器学习（包括神经网络）来预测疾病进展并确定抗青光眼手术需求的技术。文章还讨论了基于投影机器学习方法的个性化治疗方法，并概述了在解决与青光眼筛查、诊断和治疗相关的任务中使用AI的问题和前景。
