Truly privacy-preserving federated analytics for precision medicine with multiparty homomorphic encryption

Truly privacy-preserving federated analytics for precision medicine with multiparty homomorphic encryption

<jats:title>Abstract</jats:title><jats:p>Using real-world evidence in biomedical research, an indispensable complement to clinical trials, requires access to large quantities of patient data that are typically held separately by multiple healthcare institutions. We propose FAMHE, a...

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Bibliographic Details
Main Authors: Froelicher, David, Troncoso-Pastoriza, Juan R, Raisaro, Jean Louis, Cuendet, Michel A, Sousa, Joao Sa, Cho, Hyunghoon, Berger, Bonnie, Fellay, Jacques, Hubaux, Jean-Pierre
Other Authors: Massachusetts Institute of Technology. Department of Mathematics
Format: Article
Language:English
Published: Springer Science and Business Media LLC 2022
Online Access:https://hdl.handle.net/1721.1/145592

Internet

https://hdl.handle.net/1721.1/145592

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