Privacy-Preserving Generative Deep Neural Networks Support Clinical Data Sharing

BACKGROUND: Data sharing accelerates scientific progress but sharing individual-level data while preserving patient privacy presents a barrier. METHODS AND RESULTS: Using pairs of deep neural networks, we generated simulated, synthetic participants that closely resemble participants of the SPRINT tr...

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Detalles Bibliográficos
Autores principales: Beaulieu-Jones, Brett K., Wu, Zhiwei Steven, Williams, Chris, Lee, Ran, Bhavnani, Sanjeev P., Byrd, James Brian, Greene, Casey S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2019
Materias:
Methods Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7041894/
https://www.ncbi.nlm.nih.gov/pubmed/31284738
http://dx.doi.org/10.1161/CIRCOUTCOMES.118.005122

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7041894/
https://www.ncbi.nlm.nih.gov/pubmed/31284738
http://dx.doi.org/10.1161/CIRCOUTCOMES.118.005122

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