Privacy-preserving semi-parallel logistic regression training with fully homomorphic encryption
Abstract Background Privacy-preserving computations on genomic data, and more generally on medical data, is a critical path technology for innovative, life-saving research to positively and equally impact the global population. It enables medical research algorithms to be securely deployed in the cl...
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| Main Authors: | , , , |
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| Format: | Book |
| Published: |
BMC,
2020-07-01T00:00:00Z.
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| Subjects: | |
| Online Access: | Connect to this object online. |
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Internet
Connect to this object online.3rd Floor Main Library
| Call Number: |
A1234.567 |
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| Copy 1 | Available |