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Christine M. O'Keefe

Researcher at Commonwealth Scientific and Industrial Research Organisation

Publications -  103
Citations -  1931

Christine M. O'Keefe is an academic researcher from Commonwealth Scientific and Industrial Research Organisation. The author has contributed to research in topics: Health care & Ovoid. The author has an hindex of 24, co-authored 102 publications receiving 1808 citations. Previous affiliations of Christine M. O'Keefe include University of Adelaide & University of Western Australia.

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Journal ArticleDOI

Biomedical data privacy: problems, perspectives, and recent advances

TL;DR: The arrival of ultra-cheap data collection and processing technologies is fundamentally changing the face of healthcare, with clinical and administrative health data being complemented with a range of *omics data, where genomics and proteomics are currently leading the charge.
Proceedings ArticleDOI

Privacy-preserving data linkage protocols

TL;DR: This work proposes several privacy-preserving data linkage and data extraction protocols that enables data sources to generate common pseudonyms without revealing any identifying information to any party, and shows how the protocols are applicable for any number of data sources.
Journal ArticleDOI

Mining Unexpected Temporal Associations: Applications in Detecting Adverse Drug Reactions

TL;DR: The MUTARC is applied to generate adverse drug reaction (ADR) signals from real-world healthcare administrative databases and reliably shortlists not only six known ADRs, but also another ADR, flucloxacillin possibly causing hepatitis, which the algorithm designers and experiment runners have not known before the experiments.
Journal ArticleDOI

Data linkage infrastructure for cross-jurisdictional health-related research in Australia

TL;DR: The development of the processes and methodology required to create cross-jurisdictional research infrastructure and enable aggregation of State and Territory linkages into a single linkage “map” is described.
Book ChapterDOI

Multisecret threshold schemes

TL;DR: This paper considers the situation where there is a secret sK associated with each k-subset K of participants and sK can be reconstructed by any group of t participants in K (t ? k).