This paper is in the following e-collection/theme issue:

Secondary Use of Clinical Data for Research and Surveillance (248) Data Science (105) Ethics, Privacy, and Legal Issues (356) Big Data (166)

Published on in Vol 7 , No 2 (2019) :Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/12702, first published .
Privacy-Preserving Analysis of Distributed Biomedical Data: Designing Efficient and Secure Multiparty Computations Using Distributed Statistical Learning Theory

Privacy-Preserving Analysis of Distributed Biomedical Data: Designing Efficient and Secure Multiparty Computations Using Distributed Statistical Learning Theory

Privacy-Preserving Analysis of Distributed Biomedical Data: Designing Efficient and Secure Multiparty Computations Using Distributed Statistical Learning Theory

Authors of this article:

Fida K Dankar 1 Author Orcid Image ;   Nisha Madathil 1 Author Orcid Image ;   Samar K Dankar 2 Author Orcid Image ;   Sabri Boughorbel 3 Author Orcid Image
Article Authors Cited by (7) Tweetations (5) Metrics
Fida K Dankar 1 , PhD ;   Nisha Madathil 1 , MS ;   Samar K Dankar 2 , PhD ;   Sabri Boughorbel 3 , PhD

1 United Arab Emirates University , Abu Dhabi , AE

2 Independent Scientist , Ottawa , ON , CA

3 Sidra Medicine , Doha , QA

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