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
2009
Is there an advantage in scoring early embryos on more than one day?
Racowsky C, Ohno-Machado L, Kim J, Biggers J. Is there an advantage in scoring early embryos on more than one day? Human Reproduction 2009, 24: 2104-2113. PMID: 19493872, PMCID: PMC2727402, DOI: 10.1093/humrep/dep198.Peer-Reviewed Original Research
2008
Improving calibration of logistic regression models by local estimates.
Osl M, Ohno-Machado L, Baumgartner C, Tilg B, Dreiseitl S. Improving calibration of logistic regression models by local estimates. AMIA Annual Symposium Proceedings 2008, 2008: 535-9. PMID: 18998878, PMCID: PMC2656048.Peer-Reviewed Original Research
2002
Logistic regression and artificial neural network classification models: a methodology review
Dreiseitl S, Ohno-Machado L. Logistic regression and artificial neural network classification models: a methodology review. Journal Of Biomedical Informatics 2002, 35: 352-359. PMID: 12968784, DOI: 10.1016/s1532-0464(03)00034-0.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsMeSH KeywordsClassificationLogistic ModelsModels, TheoreticalNerve NetOrganization and AdministrationRegression AnalysisConceptsMedical data classification tasksNeural network classification modelArtificial neural network (ANN) classification modelData classification tasksNetwork classification modelArtificial neural networkArtificial neural network modelNeural network modelClassification taskNeural networkClassification modelNetwork modelTechnical pointMachineAlgorithmNetworkTaskQuality criteriaModelMethodology reviewSample of papers
1999
NEURAL NETWORK APPLICATIONS IN PHYSICAL MEDICINE AND REHABILITATION1
Ohno-Machado L, Rowland T. NEURAL NETWORK APPLICATIONS IN PHYSICAL MEDICINE AND REHABILITATION1. American Journal Of Physical Medicine & Rehabilitation 1999, 78: 392-398. PMID: 10418849, DOI: 10.1097/00002060-199907000-00022.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus Statements