DeepFake electrocardiograms using generative adversarial networks are the beginning of the end for p...
DeepFake electrocardiograms using generative adversarial networks are the beginning of the end for privacy issues in medicine
About this item
Full title
Author / Creator
Thambawita, Vajira , Isaksen, Jonas L. , Hicks, Steven A. , Ghouse, Jonas , Ahlberg, Gustav , Linneberg, Allan , Grarup, Niels , Ellervik, Christina , Olesen, Morten Salling , Hansen, Torben , Graff, Claus , Holstein-Rathlou, Niels-Henrik , Strümke, Inga , Hammer, Hugo L. , Maleckar, Mary M. , Halvorsen, Pål , Riegler, Michael A. and Kanters, Jørgen K.
Publisher
London: Nature Publishing Group UK
Journal title
Language
English
Formats
Publication information
Publisher
London: Nature Publishing Group UK
Subjects
More information
Scope and Contents
Contents
Recent global developments underscore the prominent role big data have in modern medical science. But privacy issues constitute a prevalent problem for collecting and sharing data between researchers. However, synthetic data generated to represent real data carrying similar information and distribution may alleviate the privacy issue. In this study...
Alternative Titles
Full title
DeepFake electrocardiograms using generative adversarial networks are the beginning of the end for privacy issues in medicine
Authors, Artists and Contributors
Author / Creator
Isaksen, Jonas L.
Hicks, Steven A.
Ghouse, Jonas
Ahlberg, Gustav
Linneberg, Allan
Grarup, Niels
Ellervik, Christina
Olesen, Morten Salling
Hansen, Torben
Graff, Claus
Holstein-Rathlou, Niels-Henrik
Strümke, Inga
Hammer, Hugo L.
Maleckar, Mary M.
Halvorsen, Pål
Riegler, Michael A.
Kanters, Jørgen K.
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_083a56ecd10843639b0fa258ef14862d
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_083a56ecd10843639b0fa258ef14862d
Other Identifiers
ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-021-01295-2
