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Secure and scalable deduplication of horizontally partitioned health data for privacy-preserving distributed statistical computation

BACKGROUND: Techniques have been developed to compute statistics on distributed datasets without revealing private information except the statistical results. However, duplicate records in a distributed dataset may lead to incorrect statistical results. Therefore, to increase the accuracy of the sta...

詳細記述

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書誌詳細
出版年:BMC Med Inform Decis Mak
主要な著者: Yigzaw, Kassaye Yitbarek, Michalas, Antonis, Bellika, Johan Gustav
フォーマット: Artigo
言語:Inglês
出版事項: BioMed Central 2017
主題:
オンライン・アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC5209873/
https://ncbi.nlm.nih.gov/pubmed/28049465
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12911-016-0389-x
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