Privacy-first health research with federated learning

Privacy protection is paramount in conducting health research. However, studies often rely on data stored in a centralized repository, where analysis is done with full access to the sensitive underlying content. Recent advances in federated learning enable building complex machine-learned models tha...

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Detalles Bibliográficos
Autores principales: Sadilek, Adam, Liu, Luyang, Nguyen, Dung, Kamruzzaman, Methun, Serghiou, Stylianos, Rader, Benjamin, Ingerman, Alex, Mellem, Stefan, Kairouz, Peter, Nsoesie, Elaine O., MacFarlane, Jamie, Vullikanti, Anil, Marathe, Madhav, Eastham, Paul, Brownstein, John S., Arcas, Blaise Aguera y., Howell, Michael D., Hernandez, John
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8423792/
https://www.ncbi.nlm.nih.gov/pubmed/34493770
http://dx.doi.org/10.1038/s41746-021-00489-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8423792/
https://www.ncbi.nlm.nih.gov/pubmed/34493770
http://dx.doi.org/10.1038/s41746-021-00489-2

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