2020
Privacy-preserving model learning on a blockchain network-of-networks
Kuo T, Kim J, Gabriel R. Privacy-preserving model learning on a blockchain network-of-networks. Journal Of The American Medical Informatics Association 2020, 27: 343-354. PMID: 31943009, PMCID: PMC7025358, DOI: 10.1093/jamia/ocz214.Peer-Reviewed Original ResearchConceptsNetwork topologyExecution timeArt methodsPredictive correctnessPrivacy-preserving learningPrivacy-preserving methodsPrivacy-preserving modelSmall training datasetBlockchain networkBlockchain platformBlockchain technologyPrivacy concernsModel learningComplex dataLearning iterationsLearning methodsTraining datasetConsensus algorithmGeneralizable predictive modelsCorrectness resultsModel disseminationHierarchical networkSmall dataHierarchical approachRecord model
2011
Anomaly and signature filtering improve classifier performance for detection of suspicious access to EHRs.
Kim J, Grillo J, Boxwala A, Jiang X, Mandelbaum R, Patel B, Mikels D, Vinterbo S, Ohno-Machado L. Anomaly and signature filtering improve classifier performance for detection of suspicious access to EHRs. AMIA Annual Symposium Proceedings 2011, 2011: 723-31. PMID: 22195129, PMCID: PMC3243249.Peer-Reviewed Original ResearchConceptsSuspicious accessAccess recordsRule-based techniquesMachine learning methodsConstruction of classifiersAnomaly detectionInformative instancesLearning methodsSymbolic clusteringClassifier performanceSignature detectionIndependent test setInappropriate accessTest setEHRFiltering methodIntegrated filtering strategyFiltering strategyClassifierFilteringNegative rateFalse negative rateAccessDetectionClustering