2017
Developing a framework for digital objects in the Big Data to Knowledge (BD2K) commons: Report from the Commons Framework Pilots workshop
Jagodnik K, Koplev S, Jenkins S, Ohno-Machado L, Paten B, Schurer S, Dumontier M, Verborgh R, Bui A, Ping P, McKenna N, Madduri R, Pillai A, Ma'ayan A. Developing a framework for digital objects in the Big Data to Knowledge (BD2K) commons: Report from the Commons Framework Pilots workshop. Journal Of Biomedical Informatics 2017, 71: 49-57. PMID: 28501646, PMCID: PMC5545976, DOI: 10.1016/j.jbi.2017.05.006.Peer-Reviewed Original ResearchConceptsBig dataDigital objectsBig data scienceNIH Big DataDiversity of dataComputational infrastructureData scienceData sharingVirtual environmentSecure processK frameworkDiverse datasetsKnowledge initiativesKnowledge commonsSuch dataBiomedical researchObjectsInteroperabilityFrameworkDiscoverabilityRecent yearsSharingDatasetInfrastructurePilot project
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
Big Data In Health Care: Using Analytics To Identify And Manage High-Risk And High-Cost Patients
Bates D, Saria S, Ohno-Machado L, Shah A, Escobar G. Big Data In Health Care: Using Analytics To Identify And Manage High-Risk And High-Cost Patients. Health Affairs 2014, 33: 1123-1131. PMID: 25006137, DOI: 10.1377/hlthaff.2014.0041.Commentaries, Editorials and LettersConceptsBig dataClinical analyticsPrivacy concernsUse casesElectronic health recordsAnalyticsTypes of dataHealth recordsTypes of insightsNecessary analysisSupport of researchHigh-cost patientsUnprecedented opportunityMonitoring devicesCostHealth careAlgorithmMultiple organ systemsRapid progressInfrastructureUS health care systemHealth care systemSystemAdverse eventsClinical dataMAGI: a Node.js web service for fast microRNA-Seq analysis in a GPU infrastructure
Kim J, Levy E, Ferbrache A, Stepanowsky P, Farcas C, Wang S, Brunner S, Bath T, Wu Y, Ohno-Machado L. MAGI: a Node.js web service for fast microRNA-Seq analysis in a GPU infrastructure. Bioinformatics 2014, 30: 2826-2827. PMID: 24907367, PMCID: PMC4173015, DOI: 10.1093/bioinformatics/btu377.Peer-Reviewed Original ResearchConceptsWeb servicesWeb reportsLarge input filesNovel feature extractionEnd performance improvementsExploration of resultsGPU infrastructureInteractive visualizationJavaScript frameworkParallel computingGPU devicesHypertext PreprocessorCUDA CFeature extractionDrop operationInput filesPlot generationSalient featuresPerformance improvementInfrastructureNodesServicesData analysisComputingBrowser
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 stakeholdersTimelinessGenomes 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 Research
1999
The decision systems group: creating a framework for decision making.
Greenes R, Boxwala A, Ohno-Machado L. The decision systems group: creating a framework for decision making. M.D. Computing 1999, 16: 23-7. PMID: 10507232.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus Statements