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Proof-of-concept study: Homomorphically encrypted data can support real-time learning in personalized cancer medicine
BACKGROUND: The successful introduction of homomorphic encryption (HE) in clinical research holds promise for improving acceptance of data-sharing protocols, increasing sample sizes, and accelerating learning from real-world data (RWD). A well-scoped use case for HE would pave the way for more wides...
Autores principales: | Paddock, Silvia, Abedtash, Hamed, Zummo, Jacqueline, Thomas, Samuel |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6894133/ https://www.ncbi.nlm.nih.gov/pubmed/31801535 http://dx.doi.org/10.1186/s12911-019-0983-9 |
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