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

Secondary Use of Clinical Data for Research and Surveillance (341) Data Science (247) Ethics, Privacy, and Legal Issues (465) Big Data (232)

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 Dankar1 Author Orcid Image ;   Nisha Madathil1 Author Orcid Image ;   Samar K Dankar2 Author Orcid Image ;   Sabri Boughorbel3 Author Orcid Image
Article Authors Cited by (21) 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, United Arab Emirates

2 Independent Scientist, Ottawa, ON, Canada

3 Sidra Medicine, Doha, Qatar

Corresponding Author: