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
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 ResearchMeSH KeywordsAlgorithmsCalibrationCluster AnalysisData Interpretation, StatisticalLogistic ModelsProportional Hazards ModelsRegression AnalysisRisk AssessmentValidation of an Automated Safety Surveillance System with Prospective, Randomized Trial Data
Matheny M, Morrow D, Ohno-Machado L, Cannon C, Sabatine M, Resnic F. Validation of an Automated Safety Surveillance System with Prospective, Randomized Trial Data. Medical Decision Making 2008, 29: 247-256. PMID: 19015285, PMCID: PMC2743924, DOI: 10.1177/0272989x08327110.Peer-Reviewed Original ResearchMeSH KeywordsBayes TheoremData Interpretation, StatisticalDecision Support TechniquesFibrinolytic AgentsHumansIntracranial HemorrhagesMulticenter Studies as TopicMyocardial InfarctionRandomized Controlled Trials as TopicReproducibility of ResultsRetrospective StudiesSafety ManagementSentinel SurveillanceConceptsIntervention armMortality rateEvent ratesTrial BTrial AMajor bleeding ratesOutcomes Surveillance SystemIntracranial hemorrhage rateCumulative event rateRandomized trial dataEvent-rate analysisSafety surveillance systemSurveillance systemAdverse eventsMulticenter trialHemorrhage rateMonth 14Bleeding rateControl armClinical trialsTrial B.Trial dataTrialsObserved event ratesMonths
2007
Validating an automated outcomes surveillance application using data from a terminated randomized, controlled trial (OPUS [TIMI-16]).
Matheny M, Morrow D, Ohno-Machado L, Cannon C, Resnic F. Validating an automated outcomes surveillance application using data from a terminated randomized, controlled trial (OPUS [TIMI-16]). AMIA Annual Symposium Proceedings 2007, 1043. PMID: 18694141.Peer-Reviewed Original Research
2005
The use of receiver operating characteristic curves in biomedical informatics
Lasko T, Bhagwat J, Zou K, Ohno-Machado L. The use of receiver operating characteristic curves in biomedical informatics. Journal Of Biomedical Informatics 2005, 38: 404-415. PMID: 16198999, DOI: 10.1016/j.jbi.2005.02.008.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsA global goodness-of-fit test for receiver operating characteristic curve analysis via the bootstrap method
Zou K, Resnic F, Talos I, Goldberg-Zimring D, Bhagwat J, Haker S, Kikinis R, Jolesz F, Ohno-Machado L. A global goodness-of-fit test for receiver operating characteristic curve analysis via the bootstrap method. Journal Of Biomedical Informatics 2005, 38: 395-403. PMID: 16198998, DOI: 10.1016/j.jbi.2005.02.004.Peer-Reviewed Original ResearchAdolescentAdultAlgorithmsAngioplasty, Balloon, CoronaryBrain NeoplasmsCalibrationData Interpretation, StatisticalDecision Support Systems, ClinicalDiagnosis, Computer-AssistedDiscriminant AnalysisExpert SystemsFemaleHumansIncidenceMaleMiddle AgedOutcome Assessment, Health CarePrognosisRisk AssessmentRisk FactorsROC CurveSurvival AnalysisSurvival RateUnited StatesCombining Classifiers Using Their Receiver Operating Characteristics and Maximum Likelihood Estimation
Haker S, Wells W, Warfield S, Talos I, Bhagwat J, Goldberg-Zimring D, Mian A, Ohno-Machado L, Zou K. Combining Classifiers Using Their Receiver Operating Characteristics and Maximum Likelihood Estimation. Lecture Notes In Computer Science 2005, 8: 506-514. PMID: 16685884, PMCID: PMC3681096, DOI: 10.1007/11566465_63.Peer-Reviewed Original Research
2002
Visualization and evaluation of clusters for exploratory analysis of gene expression data
Kim J, Kohane I, Ohno-Machado L. Visualization and evaluation of clusters for exploratory analysis of gene expression data. Journal Of Biomedical Informatics 2002, 35: 25-36. PMID: 12415724, DOI: 10.1016/s1532-0464(02)00001-1.Peer-Reviewed Original ResearchConceptsClustering algorithmDifferent clustering algorithmsPopular clustering algorithmNew clustering algorithmComprehensive data visualizationGene expression data analysisData visualization strategiesExpression data analysisEvaluation of clustersData visualizationSoftware toolsCluster qualityCluster consistencyAlgorithmActual implementationData setsGene expression dataQuality measuresVisualizationPromising resultsFrameworkData analysisObjective evaluationUsersExpression dataComparing imperfect measurements with the Bland-Altman technique: application in gene expression analysis.
Ohno-Machado L, Vinterbo S, Dreiseitl S, Jenssen T, Kuo W. Comparing imperfect measurements with the Bland-Altman technique: application in gene expression analysis. AMIA Annual Symposium Proceedings 2002, 572-6. PMID: 12463888, PMCID: PMC2244491.Peer-Reviewed Original ResearchBiasComputational BiologyData Interpretation, StatisticalGene ExpressionOligonucleotide Array Sequence AnalysisRNA, Messenger
2000
Unsupervised learning from complex data: the matrix incision tree algorithm.
Kim J, Ohno-Machado L, Kohane I. Unsupervised learning from complex data: the matrix incision tree algorithm. Biocomputing 2000, 30-41. PMID: 11262950, DOI: 10.1142/9789814447362_0004.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsArtificial IntelligenceCluster AnalysisData Interpretation, StatisticalGene Expression ProfilingHumansLeukemiaModels, GeneticOligonucleotide Array Sequence AnalysisConceptsHigh-dimensional spaceTree algorithmComplex high-dimensional spacesPredictive model buildingData setsLarge-scale gene expression dataLow-dimensional spaceKnowledge discoveryUnsupervised learningData structureComplex dataNovel methodMeaningful structuresMicroarray data setsDNA microarray data setsAlgorithm
1998
Comparison of multiple prediction models for ambulation following spinal cord injury.
Rowland T, Ohno-Machado L, Ohrn A. Comparison of multiple prediction models for ambulation following spinal cord injury. AMIA Annual Symposium Proceedings 1998, 528-32. PMID: 9929275, PMCID: PMC2232380.Peer-Reviewed Original ResearchBuilding manageable rough set classifiers.
Ohrn A, Ohno-Machado L, Rowland T. Building manageable rough set classifiers. AMIA Annual Symposium Proceedings 1998, 543-7. PMID: 9929278, PMCID: PMC2232320.Peer-Reviewed Original ResearchMeSH KeywordsClassificationData Interpretation, StatisticalDatabases, FactualDecision Support TechniquesFuzzy LogicROC CurveConceptsReal-world medical datasetsRule-based classifierRough set classifierRough set theoryKnowledge discoveryData miningMedical datasetsBoolean reasoningSet classifierSet theoryClassifierBetter performanceSmall modelsMiningAvailable informationDatasetReasoningInteresting aspectsModelCapabilityInformationSetInspectionRulesPerformance