Suppr超能文献

在保护隐私的同时发布电子健康记录数据:算法综述

Publishing data from electronic health records while preserving privacy: a survey of algorithms.

作者信息

Gkoulalas-Divanis Aris, Loukides Grigorios, Sun Jimeng

机构信息

IBM Research-Ireland, Damastown Industrial Estate, Mulhuddart, Dublin 15, Ireland.

School of Computer Science & Informatics, Cardiff University, 5 The Parade, Roath, Cardiff CF24 3AA, UK.

出版信息

J Biomed Inform. 2014 Aug;50:4-19. doi: 10.1016/j.jbi.2014.06.002. Epub 2014 Jun 14.

Abstract

The dissemination of Electronic Health Records (EHRs) can be highly beneficial for a range of medical studies, spanning from clinical trials to epidemic control studies, but it must be performed in a way that preserves patients' privacy. This is not straightforward, because the disseminated data need to be protected against several privacy threats, while remaining useful for subsequent analysis tasks. In this work, we present a survey of algorithms that have been proposed for publishing structured patient data, in a privacy-preserving way. We review more than 45 algorithms, derive insights on their operation, and highlight their advantages and disadvantages. We also provide a discussion of some promising directions for future research in this area.

摘要

电子健康记录(EHRs)的传播对于一系列医学研究非常有益,从临床试验到疫情控制研究,但必须以保护患者隐私的方式进行。这并非易事,因为传播的数据需要防范多种隐私威胁,同时还要对后续分析任务有用。在这项工作中,我们对为以隐私保护方式发布结构化患者数据而提出的算法进行了综述。我们审查了45多种算法,深入了解它们的运行情况,并突出它们的优缺点。我们还对该领域未来研究的一些有前景的方向进行了讨论。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验