Proof-of-concept study: Homomorphically encrypted data can support real-time learning in personalized cancer medicine
Abstract 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 mo...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2019-12-01
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| Series: | BMC Medical Informatics and Decision Making |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12911-019-0983-9 |