建立标准化的数据中心有利于收集高质量数据资源与促进医学人工智能的发展，在医疗大数据的基础上建立不同应用场景的医疗人工智能系统，整合、搭建可满足多种疾病诊疗需求的智能服务云平台，全面提升智能医疗管理的效率。本文以眼科为研究基础，对眼科数据中心和智能服务云平台的建设经验进行总结分析，为眼科及其他专科开展人工智能研究、建立数据中心、搭建智能服务云平台等方面提供参考。

The establishment of standardized data center can promote the accumulation of high-quality data resources and the development of medical artificial intelligence. On the basis of medical big data, medical artificial intelligence systems in different application scenarios can be established and integrated into an intelligent service cloud platform, which improves the management efficiency of intelligent medical systems. This article takes ophthalmology as a prototype to summarize the experience of the establishment of ophthalmic data center and intelligent service cloud platform, aiming to provide reference and guidance for ophthalmology and other specialties to carry out artificial intelligence research, establish data center and build an intelligent service cloud platform.

随着亚太眼科学会(Asia-Pacific Academy of Ophthalmology，APAO)永久会址和秘书处落户在中山大学中山眼科中心珠江新城院区眼科学国家重点实验室大楼(中国广州)，在大数据时代背景下，建设先进的亚太级眼科学科学数据中心已成为亚太眼科创新战略发展的需要。通过建设科学数据中心，一方面缓解眼科学国家重点实验室项目科研数据增长压力，一方面为眼科大数据与人工智能等新兴科研项目开展提供保障平台，为亚太眼科学科建设打下坚实的数据基础。科学数据中心设计建设遵照国家《科学数据管理办法》实施，以加强和规范科学数据管理，保障科学数据安全，提高开放共享水平，更好支撑国家科技创新、经济社会发展和符合国家信息安全建设方针。

As the Asia-Pacific Academy of Ophthalmology (APAO) secretariat permanently located in the building of State Key Laboratory of Ophthalmology (Guangzhou, China). In big data time, it’s a problem for the development of the Asia-pacific ophthalmology innovation strategy to construct the Asia-pacific science data center of ophthalmology. Through the construction of science data center, alleviate the pressure of the state key laboratory of ophthalmology data growth, for big data and new research fields such as artificial intelligence to provide guarantee, provided a basis for the Asia-pacific eye subject construction. Science data center construction in accordance with national “scientific data management method”, to strengthen and standardize the scientific data management, to ensure the safety of scientific data, improve the level of open sharing, better support scientific and technological innovation, economic and social development and national security as a policy.