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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Detalles Bibliográficos
Autores principales: Chen, Hao, Gilad-Bachrach, Ran, Han, Kyoohyung, Huang, Zhicong, Jalali, Amir, Laine, Kim, Lauter, Kristin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6180402/
https://www.ncbi.nlm.nih.gov/pubmed/30309350
http://dx.doi.org/10.1186/s12920-018-0397-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6180402/
https://www.ncbi.nlm.nih.gov/pubmed/30309350
http://dx.doi.org/10.1186/s12920-018-0397-z

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