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

Research output: Contribution to journalReview articlepeer-review

Aris Gkoulalas-Divanis, Grigorios Loukidis, Jimeng Sun

Original languageEnglish
Early online date14 Jun 2014
Accepted/In press5 Jun 2014
E-pub ahead of print14 Jun 2014


  • JBI_survey

    JBI_survey.pdf, 333 KB, application/pdf

    Uploaded date:15 May 2017

    Version:Accepted author manuscript

King's Authors


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.

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