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Developing High Performance Secure Multi-Party Computation Protocols in Healthcare: A Case Study of Patient Risk Stratification
2021
AMIA Annual Symposium Proceedings
We demonstrate that secure multi-party computation (MPC) using garbled circuits is viable technology for solving clinical use cases that require cross-institution data exchange and collaboration. We describe two MPC protocols, based on Yao's garbled circuits and tested using large and realistically synthesized datasets. Linking records using private set intersection (PSI), we compute two metrics often used in patient risk stratification: high utilizer identification (PSI-HU) and comorbidity
pmid:34457134
pmcid:PMC8378657
fatcat:5u72peu6nneadktlnfvxoj6j6y