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/disadvantagesA tutorial on calibration measurements and calibration models for clinical prediction models
Huang Y, Li W, Macheret F, Gabriel R, Ohno-Machado L. A tutorial on calibration measurements and calibration models for clinical prediction models. Journal Of The American Medical Informatics Association 2020, 27: 621-633. PMID: 32106284, PMCID: PMC7075534, DOI: 10.1093/jamia/ocz228.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus Statements
2017
A risk prediction score for acute kidney injury in the intensive care unit
Malhotra R, Kashani K, Macedo E, Kim J, Bouchard J, Wynn S, Li G, Ohno-Machado L, Mehta R. A risk prediction score for acute kidney injury in the intensive care unit. Nephrology Dialysis Transplantation 2017, 32: 814-822. PMID: 28402551, DOI: 10.1093/ndt/gfx026.Peer-Reviewed Original ResearchConceptsAcute kidney injuryIntensive care unitAcute risk factorsRisk score modelICU admissionKidney injuryCare unitValidation cohortKidney diseaseRisk factorsTest cohortTreatment of AKIAtherosclerotic coronary vascular diseaseMulticenter prospective cohort studyGlobal Outcomes criteriaChronic kidney diseaseHigh-risk patientsProspective cohort studyChronic liver diseaseCongestive heart failureTime of screeningCoronary vascular diseaseRisk prediction scoreEarly therapeutic interventionExternal validation cohort
2015
VERTIcal Grid lOgistic regression (VERTIGO)
Li Y, Jiang X, Wang S, Xiong H, Ohno-Machado L. VERTIcal Grid lOgistic regression (VERTIGO). Journal Of The American Medical Informatics Association 2015, 23: 570-579. PMID: 26554428, PMCID: PMC4901373, DOI: 10.1093/jamia/ocv146.Peer-Reviewed Original ResearchConceptsFederated data analysisReal-world medical classification problemsMedical classification problemsLogistic regression algorithmAccurate global modelData setsReal data setsClassification problemExchange of informationLR problemTime complexityComputational complexityExpensive operationRegression algorithmComputational costData analysisAlgorithmDual optimizationTechnical challengesLarge amountComplexityPatient recordsLR modelNovel techniqueHessian matrix
2013
WebGLORE: a Web service for Grid LOgistic REgression
Jiang W, Li P, Wang S, Wu Y, Xue M, Ohno-Machado L, Jiang X. WebGLORE: a Web service for Grid LOgistic REgression. Bioinformatics 2013, 29: 3238-3240. PMID: 24072732, PMCID: PMC3842761, DOI: 10.1093/bioinformatics/btt559.Peer-Reviewed Original ResearchConceptsWeb servicesHypertext Transfer Protocol SecurePrivacy-preserving constructionFree Software FoundationGNU General Public LicenseUse web serviceFree web serviceGeneral Public LicenseDistributed datasetsTrusted serverProtocol SecureSoftware FoundationPublic LicensePHP technologyInformation exchangeBiomedical researchersLocal statisticsServicesServletsServerSecureAjaxGlobal logistic regression modelDatasetGlobal model
2012
Doubly Optimized Calibrated Support Vector Machine (DOC-SVM): An Algorithm for Joint Optimization of Discrimination and Calibration
Jiang X, Menon A, Wang S, Kim J, Ohno-Machado L. Doubly Optimized Calibrated Support Vector Machine (DOC-SVM): An Algorithm for Joint Optimization of Discrimination and Calibration. PLOS ONE 2012, 7: e48823. PMID: 23139819, PMCID: PMC3490990, DOI: 10.1371/journal.pone.0048823.Peer-Reviewed Original ResearchSelecting cases for whom additional tests can improve prognostication.
Jiang X, Kim J, Wu Y, Wang S, Ohno-Machado L. Selecting cases for whom additional tests can improve prognostication. AMIA Annual Symposium Proceedings 2012, 2012: 1260-8. PMID: 23304404, PMCID: PMC3540468.Peer-Reviewed Original ResearchGrid Binary LOgistic REgression (GLORE): building shared models without sharing data
Wu Y, Jiang X, Kim J, Ohno-Machado L. Grid Binary LOgistic REgression (GLORE): building shared models without sharing data. Journal Of The American Medical Informatics Association 2012, 19: 758-764. PMID: 22511014, PMCID: PMC3422844, DOI: 10.1136/amiajnl-2012-000862.Peer-Reviewed Original ResearchConceptsIntegrity of communicationCentralized data sourcesTraditional LR modelCentral repositoryComputational costData sourcesData setsSame formatPatient dataComputationGenomic dataRare patternRelevant dataLR modelPrediction valueSetRepositoryPartial elementsFormatClassificationCommunicationModelDataPatient setPerform
2000
Building knowledge in a complex preterm birth problem domain.
Goodwin L, Maher S, Ohno-Machado L, Iannacchione M, Crockett P, Dreiseitl S, Vinterbo S, Hammond W. Building knowledge in a complex preterm birth problem domain. AMIA Annual Symposium Proceedings 2000, 305-9. PMID: 11079894, PMCID: PMC2243761.Peer-Reviewed Original Research
1998
Improving machine learning performance by removing redundant cases in medical data sets.
Ohno-Machado L, Fraser H, Ohrn A. Improving machine learning performance by removing redundant cases in medical data sets. AMIA Annual Symposium Proceedings 1998, 523-7. PMID: 9929274, PMCID: PMC2232167.Peer-Reviewed Original Research
1997
Sequential versus standard neural networks for pattern recognition: An example using the domain of coronary heart disease
Ohno-Machado L, Musen M. Sequential versus standard neural networks for pattern recognition: An example using the domain of coronary heart disease. Computers In Biology And Medicine 1997, 27: 267-281. PMID: 9303265, DOI: 10.1016/s0010-4825(97)00008-5.Peer-Reviewed Original ResearchMeSH KeywordsAdultAge FactorsAlgorithmsArea Under CurveBlood PressureBody WeightCause of DeathCholesterolCoronary DiseaseDatabases as TopicDemographyDisease ProgressionDisease-Free SurvivalEvaluation Studies as TopicFollow-Up StudiesForecastingHumansMaleMiddle AgedModels, CardiovascularNeural Networks, ComputerOutcome Assessment, Health CarePattern Recognition, AutomatedPrognosisROC CurveSmokingSurvival AnalysisTime FactorsConceptsNeural network modelNeural networkSequential neural network modelsTime-oriented dataNetwork modelNeural network architectureStandard neural networkSequential neural networkNeural network systemRecognition of patternsNetwork architecturePattern recognitionUnseen casesNetwork systemTest setSingle pointResearch data basesData basesNetworkMedical researchersSuch modelsRecognitionBackpropagationSetArchitecture
1996
Sequential use of neural networks for survival prediction in AIDS.
Ohno-Machado L. Sequential use of neural networks for survival prediction in AIDS. AMIA Annual Symposium Proceedings 1996, 170-4. PMID: 8947650, PMCID: PMC2233186.Peer-Reviewed Original Research