构建大数据时代的合成人群
Constructing synthetic populations in the age of big data
摘要：
为了利用微观模拟开发公共卫生干预模型，需要有关居民的广泛个人信息，如社会人口、经济和健康数字。数据保密性是这类数据的一个基本特征，而数据应支持现实的情景。此类数据的收集只能在安全的环境中进行，不能直接用于外部微观模拟模型。本文的目的是说明一种方法，通过预测个人特征的模型的基础上，对整个荷兰人口的健康和社会经济决定因素的机密数据的合成数据的建设。
英文摘要：
To develop public health intervention models using microsimulations, extensive personal information about inhabitants is needed, such as socio-demographic, economic and health figures. Data confidentiality is an essential characteristic of such data, while the data should support realistic scenarios. Collection of such data is possible only in secured environments and not directly available for external micro-simulation models. The aim of this paper is to illustrate a method for construction of synthetic data by predicting individual features through models based on confidential data on health and socio-economic determinants of the entire Dutch population.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
