Artificial intelligence in ophthalmology.

Stella Ioana Popescu Patoni, Alexandra Andreea Mihaela Muşat, Cristina Patoni, Marius-Nicolae Popescu, Mihnea Munteanu, Ioana Bianca Costache, Ruxandra Angela Pîrvulescu, Ovidiu Mușat
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Abstract

One of the fields of medicine in which artificial intelligence techniques have made progress is ophthalmology. Artificial intelligence (A.I.) applications for preventing vision loss in eye illnesses have developed quickly. Artificial intelligence uses computer programs to execute various activities while mimicking human thought. Machine learning techniques are frequently utilized in the field of ophthalmology. Ophthalmology holds great promise for advancing artificial intelligence, thanks to various digital methods like optical coherence tomography (OCT) and visual field testing. Artificial intelligence has been used in ophthalmology to treat eye conditions impairing vision, including macular holes (M.H.), age-related macular degeneration (AMD), diabetic retinopathy, glaucoma, and cataracts. The more common occurrence of these diseases has led to artificial intelligence development. It is important to get annual screenings to detect eye diseases such as glaucoma, diabetic retinopathy, and age-related macular degeneration. These conditions can cause decreased visual acuity, and it is necessary to identify any changes or progression in the disease to receive appropriate treatment. Numerous studies have been conducted based on artificial intelligence using different algorithms to improve and simplify current medical practice and for early detection of eye diseases to prevent vision loss. Abbreviations: AI = artificial intelligence, AMD = age-related macular degeneration, ANN = artificial neural networks, AAO = American Academy of Ophthalmology, CNN = convolutional neural network, DL = deep learning, DVP = deep vascular plexus, FDA = Food and Drug Administration, GCL = ganglion cell layer, IDP = Iowa Detection Program, ML = Machine learning techniques, MH = macular holes, MTANN = massive training of the artificial neural network, NLP = natural language processing methods, OCT = optical coherence tomography, RBS = Radial Basis Function, RNFL = nerve fiber layer, ROP = Retinopathy of Prematurity, SAP = standard automated perimetry, SVP = Superficial vascular plexus, U.S. = United States, VEGF = vascular endothelial growth factor.

眼科学中的人工智能。
人工智能技术取得进展的医学领域之一是眼科。人工智能在预防眼病视力下降方面的应用发展迅速。人工智能使用计算机程序来执行各种活动,同时模仿人类的思想。机器学习技术经常用于眼科领域。由于光学相干断层扫描(OCT)和视野测试等各种数字方法,眼科在推进人工智能方面前景广阔。人工智能已被用于眼科治疗损害视力的眼部疾病,包括黄斑裂孔(M.H.)、年龄相关性黄斑变性(AMD)、糖尿病视网膜病变、青光眼和白内障。这些疾病的普遍发生导致了人工智能的发展。每年进行筛查以检测青光眼、糖尿病视网膜病变和年龄相关性黄斑变性等眼病是很重要的。这些情况会导致视力下降,有必要确定疾病的任何变化或进展,以便接受适当的治疗。已经基于人工智能进行了大量研究,使用不同的算法来改进和简化当前的医疗实践,并用于早期检测眼病以防止视力下降。缩写:AI=人工智能,AMD=年龄相关性黄斑变性,ANN=人工神经网络,AAO=美国眼科学会,CNN=卷积神经网络,DL=深度学习,DVP=深血管丛,FDA=食品药品监督管理局,GCL=神经节细胞层,IDP=爱荷华州检测计划,ML=机器学习技术,MH=黄斑孔,MTANN=人工神经网络的大规模训练,NLP=自然语言处理方法,OCT=光学相干断层扫描,RBS=径向基函数,RNFL=神经纤维层,ROP=早产视网膜病变,SAP=标准自动视野,SVP=浅表血管丛,U.S.=美国,VEGF=血管内皮生长因子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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