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

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

Abstract 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 prom...

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Detalles Bibliográficos
Autores principales: Jinsung Yoon, Michel Mizrahi, Nahid Farhady Ghalaty, Thomas Jarvinen, Ashwin S. Ravi, Peter Brune, Fanyu Kong, Dave Anderson, George Lee, Arie Meir, Farhana Bandukwala, Elli Kanal, Sercan Ö. Arık, Tomas Pfister
Formato: Artículo
Lenguaje:English
Publicado: Nature Portfolio 2023-08-01
Colección:npj Digital Medicine
Acceso en línea:https://doi.org/10.1038/s41746-023-00888-7

Internet

https://doi.org/10.1038/s41746-023-00888-7

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