Daien V, Muyl-Cipollina A
Service d'ophtalmologique, hôpital Gui De Chauliac, 80, avenue Augustin Fliche, 34295 Montpellier, France; Inserm, epidemiological and clinical research, université Montpellier, 34295 Montpellier, France; The Save Sight Institute, Sydney Medical School, The University of Sydney, Sydney, Australie.
Service d'ophtalmologique, hôpital Gui De Chauliac, 80, avenue Augustin Fliche, 34295 Montpellier, France.
J Fr Ophtalmol. 2019 Jun;42(6):551-571. doi: 10.1016/j.jfo.2018.11.013. Epub 2019 Apr 9.
The European Medicines Agency has defined Big Data by the "3 V's": Volume, Velocity and Variety. These large databases allow access to real life data on patient care. They are particularly suited for studies of adverse events and pharmacoepidemiology. Deep learning is a collection of algorithms used in machine learning, used to model high-level abstractions in data using model architectures, which are composed of multiple nonlinear transformations. This article shows how Big Data and Deep Learning can help in ophthalmology, pointing out their advantages and disadvantages. A literature review is presented in this article illustrating the uses of Deep Learning in ophthalmology.
欧洲药品管理局通过“3V”（即体量、速度和多样性）来定义大数据。这些大型数据库允许获取有关患者护理的真实生活数据。它们特别适用于不良事件和药物流行病学研究。深度学习是机器学习中使用的一组算法，用于使用由多个非线性变换组成的模型架构对数据中的高级抽象进行建模。本文展示了大数据和深度学习如何在眼科中发挥作用，指出了它们的优缺点。本文还进行了文献综述，阐述了深度学习在眼科中的应用。
