2022
The evolving privacy and security concerns for genomic data analysis and sharing as observed from the iDASH competition
Kuo T, Jiang X, Tang H, Wang X, Harmanci A, Kim M, Post K, Bu D, Bath T, Kim J, Liu W, Chen H, Ohno-Machado L. The evolving privacy and security concerns for genomic data analysis and sharing as observed from the iDASH competition. Journal Of The American Medical Informatics Association 2022, 29: 2182-2190. PMID: 36164820, PMCID: PMC9667175, DOI: 10.1093/jamia/ocac165.Peer-Reviewed Original ResearchConceptsSensitive personal informationGenomic data analysisPotential future research directionsPersonal informationSecurity concernsGenomics data repositoryData repositoryReport lessonsProtection techniquesFuture research directionsPrivacyResearch directionsData usePractical challengesGenomic dataData analysisAnonymizationCommunity effortsRepositorySecurityBiomedical researchInformationDataChallenges
2020
The Data Tags Suite (DATS) model for discovering data access and use requirements
Alter G, Gonzalez-Beltran A, Ohno-Machado L, Rocca-Serra P. The Data Tags Suite (DATS) model for discovering data access and use requirements. GigaScience 2020, 9: giz165. PMID: 32031623, PMCID: PMC7006671, DOI: 10.1093/gigascience/giz165.Peer-Reviewed Original ResearchConceptsData accessData discovery toolsPrivacy of subjectsData use agreementsConfidential dataMetadata itemsData reuseMetadata schemaAutomated systemDiscovery toolTechnical systemsStandard wayUse agreementsAccessPrivacyMetadataSchemaUse requirementsReuseResearchersResearch dataSystemRequirementsInformationData
2018
Genomics and electronic health record systems
Ohno-Machado L, Kim J, Gabriel R, Kuo G, Hogarth M. Genomics and electronic health record systems. Human Molecular Genetics 2018, 27: r48-r55. PMID: 29741693, PMCID: PMC5946823, DOI: 10.1093/hmg/ddy104.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsElectronic health recordsHigh-level viewElectronic health record systemsHealth record systemsNext generation systemsEHR systemsSeamless fashionOpen issuesMyriad of approachesHealth recordsRecord systemSpecific solutionsEnd goalSources of informationAnalysis of genomesInformationCustomizationSystemGeneration systemVisionDegrees of successFunctionality
2016
PRINCESS: Privacy-protecting Rare disease International Network Collaboration via Encryption through Software guard extensionS
Chen F, Wang S, Jiang X, Ding S, Lu Y, Kim J, Sahinalp S, Shimizu C, Burns J, Wright V, Png E, Hibberd M, Lloyd D, Yang H, Telenti A, Bloss C, Fox D, Lauter K, Ohno-Machado L. PRINCESS: Privacy-protecting Rare disease International Network Collaboration via Encryption through Software guard extensionS. Bioinformatics 2016, 33: 871-878. PMID: 28065902, PMCID: PMC5860394, DOI: 10.1093/bioinformatics/btw758.Peer-Reviewed Original ResearchConceptsSoftware Guard ExtensionsHomomorphic encryptionDistributed ComputationCollaboration frameworkTrustworthy computationCollaboration modelSupplementary dataNetwork collaborationEncryptionExperimental resultsHealth informationAlternative solutionComputationInternational collaboration frameworkHardwareAccurate analysisPerformanceBioinformaticsImplementationFrameworkDataExtensionInformationCollaborationGenome privacy: challenges, technical approaches to mitigate risk, and ethical considerations in the United States
Wang S, Jiang X, Singh S, Marmor R, Bonomi L, Fox D, Dow M, Ohno‐Machado L. Genome privacy: challenges, technical approaches to mitigate risk, and ethical considerations in the United States. Annals Of The New York Academy Of Sciences 2016, 1387: 73-83. PMID: 27681358, PMCID: PMC5266631, DOI: 10.1111/nyas.13259.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsData privacySensitive individual informationComputer science communityReal-world problemsUnauthorized partiesHuman genomic dataPrivacy breachesData accessData sharingData accessibilityConfidentiality protectionGenomic dataSpectrum of techniquesIndividual informationPrivacyScience communityPhenotype informationTechnical approachPotential solutionsCurrent common practiceBiomedical researchResearch purposesConfidentialityInformationSharingSecure 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
2015
Comparison of consumers’ views on electronic data sharing for healthcare and research
Kim K, Joseph J, Ohno-Machado L. Comparison of consumers’ views on electronic data sharing for healthcare and research. Journal Of The American Medical Informatics Association 2015, 22: 821-830. PMID: 25829461, PMCID: PMC5009901, DOI: 10.1093/jamia/ocv014.Peer-Reviewed Original ResearchConceptsElectronic data sharingData sharingHealth information exchangeData networksHealth informationTechnology infrastructureInformation exchangePrivacyHealth Insurance PortabilitySharingAccountability ActUse of dataInsurance PortabilitySecurityNetworkInformationHealthcareIndividual controlHealthcare deliveryMere relianceDepth studyPortabilityAccessInfrastructureComparison of consumers
2014
PhenDisco: phenotype discovery system for the database of genotypes and phenotypes
Doan S, Lin K, Conway M, Ohno-Machado L, Hsieh A, Feupe S, Garland A, Ross M, Jiang X, Farzaneh S, Walker R, Alipanah N, Zhang J, Xu H, Kim H. PhenDisco: phenotype discovery system for the database of genotypes and phenotypes. Journal Of The American Medical Informatics Association 2014, 21: 31-36. PMID: 23989082, PMCID: PMC3912702, DOI: 10.1136/amiajnl-2013-001882.Peer-Reviewed Original ResearchConceptsNew information retrieval systemInformation retrieval systemsInformation retrieval toolsDatabase of GenotypesText processing toolsRetrieval systemSearch scenariosDiscovery systemRetrieval toolsAuthorized usersNon-standardized wayCross-study validationSearch comparisonProcessing toolsPromising performanceUsersPhenotype informationDatabaseInformationBiotechnology InformationQueriesMetadataEntrezResourcesSystem
2013
Data governance requirements for distributed clinical research networks: triangulating perspectives of diverse stakeholders
Kim K, Browe D, Logan H, Holm R, Hack L, Ohno-Machado L. Data governance requirements for distributed clinical research networks: triangulating perspectives of diverse stakeholders. Journal Of The American Medical Informatics Association 2013, 21: 714-719. PMID: 24302285, PMCID: PMC4078279, DOI: 10.1136/amiajnl-2013-002308.Peer-Reviewed Original ResearchConceptsFair Information Practice PrinciplesTechnical infrastructureClinical data reuseGovernance requirementsTrustworthy platformData reuseHealth Insurance PortabilityHIPAA regulationsAccountability ActNetworkInsurance PortabilityHealth informationRequirementsInformationResearch NetworkPrivacyPortabilityBest practicesInfrastructurePlatformReuseDiverse stakeholdersTimelinessNatural language processing: algorithms and tools to extract computable information from EHRs and from the biomedical literature
Ohno-Machado L, Nadkarni P, Johnson K. Natural language processing: algorithms and tools to extract computable information from EHRs and from the biomedical literature. Journal Of The American Medical Informatics Association 2013, 20: 805-805. PMID: 23935077, PMCID: PMC3756279, DOI: 10.1136/amiajnl-2013-002214.Commentaries, Editorials and LettersEXpectation 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 distributionServicesClientsUpdatingFrameworkFlexibilityModelPerformanceGenomes in the cloud: balancing privacy rights and the public good.
Ohno-Machado L, Farcas C, Kim J, Wang S, Jiang X. Genomes in the cloud: balancing privacy rights and the public good. AMIA Joint Summits On Translational Science Proceedings 2013, 2013: 128. PMID: 24303320.Peer-Reviewed Original ResearchIdentifying inference attacks against healthcare data repositories.
Vaidya J, Shafiq B, Jiang X, Ohno-Machado L. Identifying inference attacks against healthcare data repositories. AMIA Joint Summits On Translational Science Proceedings 2013, 2013: 262-6. PMID: 24303279, PMCID: PMC3845790.Peer-Reviewed Original Research
2012
Data Locked Inside Databases: A Text Classification In The Database Of Genotypes And Phenotypes (dbGaP) To Address Challenges In Retrieving Clinical Information From Public Data Repositories
Ross M, Kim J, Lin K, Ohno-Machado L, Finn P, Kim H. Data Locked Inside Databases: A Text Classification In The Database Of Genotypes And Phenotypes (dbGaP) To Address Challenges In Retrieving Clinical Information From Public Data Repositories. 2012, a5777-a5777. DOI: 10.1164/ajrccm-conference.2012.185.1_meetingabstracts.a5777.Peer-Reviewed Original ResearchCalibrating predictive model estimates to support personalized medicine
Jiang X, Osl M, Kim J, Ohno-Machado L. Calibrating predictive model estimates to support personalized medicine. Journal Of The American Medical Informatics Association 2012, 19: 263-274. PMID: 21984587, PMCID: PMC3277613, DOI: 10.1136/amiajnl-2011-000291.Peer-Reviewed Original ResearchConceptsReal-world medical classification problemsMedical classification problemsClassification problemPredictive model estimatesComputational complexityACP algorithmIsotonic regressionPredictive modelTerms of areaImportant performance measuresCalibration methodAdaptive techniqueCalculation of CIsAdaptive calibrationSquared errorIndividual predictionsPerformance measuresFit testInformationNew calibration methodCurrent methods
2007
MODELING CANCER: INTEGRATION OF "OMICS" INFORMATION IN DYNAMIC SYSTEMS
STRANSKY B, BARRERA J, OHNO-MACHADO L, DE SOUZA S. MODELING CANCER: INTEGRATION OF "OMICS" INFORMATION IN DYNAMIC SYSTEMS. Journal Of Bioinformatics And Computational Biology 2007, 5: 977-986. PMID: 17787066, DOI: 10.1142/s0219720007002990.Peer-Reviewed Original Research
2004
Protecting patient privacy by quantifiable control of disclosures in disseminated databases
Ohno-Machado L, Silveira P, Vinterbo S. Protecting patient privacy by quantifiable control of disclosures in disseminated databases. International Journal Of Medical Informatics 2004, 73: 599-606. PMID: 15246040, DOI: 10.1016/j.ijmedinf.2004.05.002.Peer-Reviewed Original ResearchConceptsSensitive patient dataPattern recognition algorithmsLevel of confidentialitySensitive dataPrivacy protectionSensitive informationDisseminated dataRecognition algorithmDegree of anonymityPatient privacyAlgorithmPrivacyPatient dataDatabaseAnonymizationQuantifiable controlPublic health purposesConfidentialityInformationAnonymityHealth care organizationsHealth purposesCare organizationsCommon practiceAmbiguation
2002
Disambiguation Data: Extracting Information from Anonymized Sources
Dreiseitl S, Vinterbo S, Ohno-Machado L. Disambiguation Data: Extracting Information from Anonymized Sources. Journal Of The American Medical Informatics Association 2002, 9: s110-s114. PMCID: PMC419432, DOI: 10.1197/jamia.m1240.Peer-Reviewed Original Research
2001
Disambiguation data: extracting information from anonymized sources.
Dreiseitl S, Vinterbo S, Ohno-Machado L. Disambiguation data: extracting information from anonymized sources. AMIA Annual Symposium Proceedings 2001, 144-8. PMID: 11825171, PMCID: PMC2243291.Peer-Reviewed Original Research
1999
Using Boolean reasoning to anonymize databases
Øhrn A, Ohno-Machado L. Using Boolean reasoning to anonymize databases. Artificial Intelligence In Medicine 1999, 15: 235-254. PMID: 10206109, DOI: 10.1016/s0933-3657(98)00056-6.Peer-Reviewed Original ResearchConceptsBoolean reasoningMedical data repositoriesMeasure of anonymitySensitive dataPrivacy issuesDatabase fieldAmount of trustConfidential informationDegree of anonymityData repositoryDeterministic inferenceIndividual objectsAnonymityParticular pieceAlgorithmElectronic medical recordsSpecific needsReasoningDatabasePossible misuseAnonymizationInformationRepositoryOutside worldIssues