2021
Calibrating predictive model estimates in a distributed network of patient data
Huang Y, Jiang X, Gabriel R, Ohno-Machado L. Calibrating predictive model estimates in a distributed network of patient data. Journal Of Biomedical Informatics 2021, 117: 103758. PMID: 33811986, DOI: 10.1016/j.jbi.2021.103758.Peer-Reviewed Original ResearchConceptsData privacyRecalibration modelHigh-performance predictive modelsIntegration of dataPatient dataPredictive model estimatesDistributed networkExpected calibration errorMaximum calibration errorPrivacyClinical informaticsCalibration errorsComputational efficiencyPredictive analysisAlgorithmBuilding modelsModel buildingImportant issuePerformance measuresPredictive modelMultiple health systemsLarge numberIsotonic regressionInformaticsSystem
2020
A 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
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
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 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
2007
Effects of SVM parameter optimization on discrimination and calibration for post-procedural PCI mortality
Matheny M, Resnic F, Arora N, Ohno-Machado L. Effects of SVM parameter optimization on discrimination and calibration for post-procedural PCI mortality. Journal Of Biomedical Informatics 2007, 40: 688-697. PMID: 17600771, PMCID: PMC2170520, DOI: 10.1016/j.jbi.2007.05.008.Peer-Reviewed Original ResearchConceptsSupport vector machineRadial Basis Kernel Support Vector MachineKernel support vector machineCross-entropy errorSVM parameter optimizationUnseen test dataSVM kernel typesTraining dataVector machineEvolutionary algorithmGrid searchMean squared errorKernel typeMachineOptimization methodPrediction modelNumber of methodsParameter optimizationTest dataMedical applicationsOptimization parametersMortality prediction modelAlgorithmBest modelApplications
2005
Discrimination and calibration of mortality risk prediction models in interventional cardiology
Matheny M, Ohno-Machado L, Resnic F. Discrimination and calibration of mortality risk prediction models in interventional cardiology. Journal Of Biomedical Informatics 2005, 38: 367-375. PMID: 16198996, DOI: 10.1016/j.jbi.2005.02.007.Peer-Reviewed Original ResearchMeSH KeywordsAngioplasty, Balloon, CoronaryCalibrationCardiologyComorbidityDecision Support Systems, ClinicalDiagnosis, Computer-AssistedDiscriminant AnalysisExpert SystemsHumansIncidenceOutcome Assessment, Health CarePostoperative ComplicationsPrognosisRetrospective StudiesRisk AssessmentRisk FactorsROC CurveSurvival AnalysisSurvival RateUnited StatesConceptsLocal risk modelAcute myocardial infarctionHosmer-Lemeshow goodnessRisk prediction modelRisk factorsCardiology-National Cardiovascular Data RegistryConsecutive percutaneous coronary interventionsMortality risk prediction modelPercutaneous coronary interventionMultivariate risk factorsCertain risk factorsROC curveAccurate risk predictionIndividual casesGood discriminationCardiogenic shockHospital mortalityCoronary interventionUnstable anginaArtery interventionPatient populationMyocardial infarctionRisk modelElective proceduresWomen's HospitalA 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 States