人工智能和神经网络在青光眼诊断中的应用

D. A. Dorofeev, S. Y. Kazanova, A. Movsisyan, R. P. Poleva
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引用次数: 0

摘要

青光眼的早期诊断和对仪器研究数据的客观分析是眼科学的重要问题之一。现代技术发展水平允许在青光眼的诊断和治疗中实施人工智能和神经网络。特殊的软件有助于使用便携式设备进行视野检查,这减少了医疗机构的工作量,降低了手术成本。数学模型允许基于仪器结果评估青光眼进展的风险。人工智能允许评估Goldman和Maklakov血压计的结果,并通过单独分析一系列2D和3D数据(视神经头扫描图像、静态视距等),以及对来自各种设备的数据进行复杂分析,确定疾病进展的状态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial intelligence and neural networks in the diagnosis of glaucoma
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.
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