2022
Feasibility Analysis of Phenotype Quantification from Unstructured Clinical Interactions
Barron D, Heisig S, Agurto C, Norel R, Quagan B, Powers A, Birnbaum M, Constable T, Cecchi G, Krystal J. Feasibility Analysis of Phenotype Quantification from Unstructured Clinical Interactions. Computational Psychiatry 2022, 6: 1. PMID: 38774775, PMCID: PMC11104416, DOI: 10.5334/cpsy.78.Peer-Reviewed Original Research
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
2019
Prediction Analysis for Microbiome Sequencing Data
Wang T, Yang C, Zhao H. Prediction Analysis for Microbiome Sequencing Data. Biometrics 2019, 75: 875-884. PMID: 30994187, DOI: 10.1111/biom.13061.Peer-Reviewed Original ResearchConceptsMonte Carlo expectation-maximization algorithmInverse regression modelReal data exampleTypes of covariatesNew statistical frameworkMaximum likelihood estimationExpectation-maximization algorithmDimension reduction structureInverse regressionStatistical frameworkData examplesStatistical challengesLikelihood estimationMicrobiome sequencing dataHuman microbiome studiesHuman microbiome compositionDifferent library sizesZerosPredictive analysisModelEstimationAlgorithmSimulationsRegression modelsFramework
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