EHR-Safe: generating high-fidelity and privacy-preserving synthetic electronic health records

Privacy concerns often arise as the key bottleneck for the sharing of data between consumers and data holders, particularly for sensitive data such as Electronic Health Records (EHR). This impedes the application of data analytics and ML-based innovations with tremendous potential. One promising app...

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Detalles Bibliográficos
Autores principales: Yoon, Jinsung, Mizrahi, Michel, Ghalaty, Nahid Farhady, Jarvinen, Thomas, Ravi, Ashwin S., Brune, Peter, Kong, Fanyu, Anderson, Dave, Lee, George, Meir, Arie, Bandukwala, Farhana, Kanal, Elli, Arık, Sercan Ö., Pfister, Tomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10421926/
https://www.ncbi.nlm.nih.gov/pubmed/37567968
http://dx.doi.org/10.1038/s41746-023-00888-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10421926/
https://www.ncbi.nlm.nih.gov/pubmed/37567968
http://dx.doi.org/10.1038/s41746-023-00888-7

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