2025
Distributed cross-learning for equitable federated models - privacy-preserving prediction on data from five California hospitals
Kuo T, Gabriel R, Koola J, Schooley R, Ohno-Machado L. Distributed cross-learning for equitable federated models - privacy-preserving prediction on data from five California hospitals. Nature Communications 2025, 16: 1371. PMID: 39910076, PMCID: PMC11799213, DOI: 10.1038/s41467-025-56510-9.Peer-Reviewed Original ResearchConceptsHeart disease dataParts of informationLearning counterpartsCentralized solutionVertical scenariosPatient privacyPredictive analyticsFederated modelSynchronization timePrivacyUC San DiegoPatient-level recordsDisease dataPatient dataPrediction modelPatient careHealthcare centersUniversity of CaliforniaCalifornia hospitalsHealthcare systemQuality improvementPatient records
2015
A system to build distributed multivariate models and manage disparate data sharing policies: implementation in the scalable national network for effectiveness research
Meeker D, Jiang X, Matheny M, Farcas C, D’Arcy M, Pearlman L, Nookala L, Day M, Kim K, Kim H, Boxwala A, El-Kareh R, Kuo G, Resnic F, Kesselman C, Ohno-Machado L. A system to build distributed multivariate models and manage disparate data sharing policies: implementation in the scalable national network for effectiveness research. Journal Of The American Medical Informatics Association 2015, 22: 1187-1195. PMID: 26142423, PMCID: PMC4639714, DOI: 10.1093/jamia/ocv017.Peer-Reviewed Original ResearchConceptsFederated networkData sharing policiesParallel computation methodSharing policiesPolicy management systemData exchange policiesData storage requirementsWeb servicesNetwork queriesQuery functionalityComputation resourcesFederated modelGraphical interfaceData transportCentralized networkStorage requirementsNetwork participantsManagement systemQueriesNetworkComputation methodNew featuresMultivariate statistical estimationDifferent state lawsImportant new feature
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