SCOR: A secure international informatics infrastructure to investigate COVID-19.

Details

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State: Public
Version: Final published version
License: CC BY-NC 4.0
Serval ID
serval:BIB_7D30526235EB
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
SCOR: A secure international informatics infrastructure to investigate COVID-19.
Journal
Journal of the American Medical Informatics Association
Author(s)
Raisaro J.L., Marino F., Troncoso-Pastoriza J., Beau-Lejdstrom R., Bellazzi R., Murphy R., Bernstam E.V., Wang H., Bucalo M., Chen Y., Gottlieb A., Harmanci A., Kim M., Kim Y., Klann J., Klersy C., Malin B.A., Méan M., Prasser F., Scudeller L., Torkamani A., Vaucher J., Puppala M., Wong STC, Frenkel-Morgenstern M., Xu H., Musa B.M., Habib A.G., Cohen T., Wilcox A., Salihu H.M., Sofia H., Jiang X., Hubaux J.P.
ISSN
1527-974X (Electronic)
ISSN-L
1067-5027
Publication state
Published
Issued date
01/11/2020
Peer-reviewed
Oui
Volume
27
Number
11
Pages
1721-1726
Language
english
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't
Publication Status: ppublish
Abstract
Global pandemics call for large and diverse healthcare data to study various risk factors, treatment options, and disease progression patterns. Despite the enormous efforts of many large data consortium initiatives, scientific community still lacks a secure and privacy-preserving infrastructure to support auditable data sharing and facilitate automated and legally compliant federated analysis on an international scale. Existing health informatics systems do not incorporate the latest progress in modern security and federated machine learning algorithms, which are poised to offer solutions. An international group of passionate researchers came together with a joint mission to solve the problem with our finest models and tools. The SCOR Consortium has developed a ready-to-deploy secure infrastructure using world-class privacy and security technologies to reconcile the privacy/utility conflicts. We hope our effort will make a change and accelerate research in future pandemics with broad and diverse samples on an international scale.
Keywords
Biomedical Research, COVID-19, Computer Security, Coronavirus Infections, Humans, Information Dissemination/ethics, Internationality, Machine Learning, Pandemics, Pneumonia, Viral, Privacy, federated learning, healthcare privacy, international consortium, secure data analysis
Pubmed
Web of science
Open Access
Yes
Create date
19/09/2020 13:51
Last modification date
15/01/2021 8:10
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