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Logistic regression over encrypted data from fully homomorphic encryption

BACKGROUND: One of the tasks in the 2017 iDASH secure genome analysis competition was to enable training of logistic regression models over encrypted genomic data. More precisely, given a list of approximately 1500 patient records, each with 18 binary features containing information on specific muta...

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Bibliografische gegevens
Gepubliceerd in:BMC Med Genomics
Hoofdauteurs: Chen, Hao, Gilad-Bachrach, Ran, Han, Kyoohyung, Huang, Zhicong, Jalali, Amir, Laine, Kim, Lauter, Kristin
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: BioMed Central 2018
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Online toegang:https://ncbi.nlm.nih.gov/pmc/articles/PMC6180402/
https://ncbi.nlm.nih.gov/pubmed/30309350
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12920-018-0397-z
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