2020
EXpectation Propagation LOgistic REgRession on permissioned blockCHAIN (ExplorerChain): decentralized online healthcare/genomics predictive model learning
Kuo T, Gabriel R, Cidambi K, Ohno-Machado L. EXpectation Propagation LOgistic REgRession on permissioned blockCHAIN (ExplorerChain): decentralized online healthcare/genomics predictive model learning. Journal Of The American Medical Informatics Association 2020, 27: 747-756. PMID: 32364235, PMCID: PMC7309256, DOI: 10.1093/jamia/ocaa023.Peer-Reviewed Original ResearchConceptsBlockchain technologyCentral serverServer-based methodBenefits of blockchainData protection policiesCentralized serverArtificial intelligenceModel learningDecentralized approachSmall datasetsBlockchainServerComputation strategySingle pointGeneralizable modelCost of efficiencyGenomic datasetsDatasetDistributed modelTechnologyGenomic dataMultiple institutionsDiscrimination powerIntelligencePotential advantages/disadvantages
2016
Secure Multi-pArty Computation Grid LOgistic REgression (SMAC-GLORE)
Shi H, Jiang C, Dai W, Jiang X, Tang Y, Ohno-Machado L, Wang S. Secure Multi-pArty Computation Grid LOgistic REgression (SMAC-GLORE). BMC Medical Informatics And Decision Making 2016, 16: 89. PMID: 27454168, PMCID: PMC4959358, DOI: 10.1186/s12911-016-0316-1.Peer-Reviewed Original ResearchConceptsData sharingPatient privacySecure multi-party computationModel learning phaseMulti-party computationBiomedical data sharingInformation leakageModel learningIntermediary informationInformation exchangeSecondary usePrivacyBig concernPractical solutionLogistic regression frameworkExperimental resultsSharingRegression frameworkFrameworkMultiple institutionsPrevious workComputationLearningBiomedical researchInformation
2013
EXpectation Propagation LOgistic REgRession (EXPLORER): Distributed privacy-preserving online model learning
Wang S, Jiang X, Wu Y, Cui L, Cheng S, Ohno-Machado L. EXpectation Propagation LOgistic REgRession (EXPLORER): Distributed privacy-preserving online model learning. Journal Of Biomedical Informatics 2013, 46: 480-496. PMID: 23562651, PMCID: PMC3676314, DOI: 10.1016/j.jbi.2013.03.008.Peer-Reviewed Original ResearchConceptsHigh-level guaranteesOnline model learningSensitive informationModel learningEntire dataOnline learningAbsence of participantsMore flexibilitySame performanceExperimental resultsLearningCommunicationServerInformationGuaranteesModel updatingPosterior distributionServicesClientsUpdatingFrameworkFlexibilityModelPerformance