Wu Jo-Hsuan, Lin Shan, Moghimi Sasan
Hamilton Glaucoma Center, Shiley Eye Institute and Viterbi Family Department of Ophthalmology, University of California San Diego, La Jolla, CA, United States.
Glaucoma Center of San Francisco, San Francisco, CA, United States.
Taiwan J Ophthalmol. 2023 Jul 28;14(3):333-339. doi: 10.4103/tjo.TJO-D-23-00068. eCollection 2024 Jul-Sep.
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.
眼科一直处于大数据医学应用的前沿。大数据通常与机器学习方法结合使用,已显示出改变眼科护理的潜力,通过视网膜图像筛查眼科疾病和病变等临床任务的先前成功就证明了这一点。随着近期各种大型眼科数据集的建立,人们对确定大数据的益处是否可以扩展到眼科疾病管理的下游过程产生了更大的兴趣。一个大量研究的领域是利用大数据来帮助指导或简化青光眼的管理,青光眼仍然是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的相关研究,并讨论了这些研究结果在青光眼风险评估和治疗中的应用。