Big data to guide glaucoma treatment.

IF 1 Q4 OPHTHALMOLOGY
Taiwan Journal of Ophthalmology Pub Date : 2023-07-28 eCollection Date: 2024-07-01 DOI:10.4103/tjo.TJO-D-23-00068
Jo-Hsuan Wu, Shan Lin, Sasan Moghimi
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引用次数: 0

Abstract

Ophthalmology has been at the forefront of the medical application of big data. Often harnessed with a machine learning approach, big data has demonstrated potential to transform ophthalmic care, as evidenced by prior success on clinical tasks such as the screening of ophthalmic diseases and lesions via retinal images. With the recent establishment of various large ophthalmic datasets, there has been greater interest in determining whether the benefits of big data may extend to the downstream process of ophthalmic disease management. An area of substantial investigation has been the use of big data to help guide or streamline management of glaucoma, which remains a leading cause of irreversible blindness worldwide. In this review, we summarize relevant studies utilizing big data and discuss the application of the findings in the risk assessment and treatment of glaucoma.

大数据指导青光眼治疗。
眼科一直处于大数据医疗应用的前沿。大数据通常采用机器学习方法,在临床任务(如通过视网膜图像筛查眼科疾病和病变)中取得的成功证明了大数据具有改变眼科护理的潜力。最近,随着各种大型眼科数据集的建立,人们对确定大数据的优势是否可以扩展到眼科疾病管理的下游流程产生了更大的兴趣。利用大数据帮助指导或简化青光眼的管理是一项重要的研究领域,青光眼仍然是导致全球不可逆失明的主要原因。在这篇综述中,我们总结了利用大数据进行的相关研究,并讨论了研究结果在青光眼风险评估和治疗中的应用。
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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来源期刊
CiteScore
1.80
自引率
9.10%
发文量
68
审稿时长
19 weeks
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