ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science
Developing High Performance Secure Multi-Party Computation Protocols in Healthcare: A Case Study of Patient Risk Stratification.
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 8 citations in OpenAlex.
- Reimagining paediatric care: technology, trust, and the global movement for child-centred innovation.Frontiers in medicine · 2026Review
- Addressing contemporary threats in anonymised healthcare data using privacy engineering.NPJ digital medicine · 2025Review
- Privacy-Preserving Blockchain Technologies.Sensors (Basel, Switzerland) · 2023Review
- Ten Topics to Get Started in Medical Informatics Research.Journal of medical Internet research · 2023Article
- Assessing the impact of privacy-preserving record linkage on record overlap and patient demographic and clinical characteristics in PCORnet®, the National Patient-Centered Clinical Research Network.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- New Approach to Privacy-Preserving Clinical Decision Support Systems for HIV Treatment.Journal of medical systems · 2022Article
- High performance of privacy-preserving acute myocardial infarction auxiliary diagnosis based on federated learning: a multicenter retrospective study.Annals of translational medicine · 2022Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
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 index calculation (PSI-CI). Cuckoo hashing enables our protocols to achieve extremely fast run times, with answers to clinically meaningful questions produced in minutes instead of hours. Also, our protocols are provably secure against any computationally bounded adversary in a semi-honest setting, the de-facto mode for cross-institution data analytics. Finally, these protocols eliminate the need for an implicitly trusted third-party "honest broker" to mediate the information linkage and exchange.
Indexed as
Identifiers
34457134PMC8378657W3198739380What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.