Balancing the efforts of chart review and gains in PRS prediction accuracy: An empirical study
Lei Y, Christian Naj A, Xu H, Li R, Chen Y. Balancing the efforts of chart review and gains in PRS prediction accuracy: An empirical study. Journal Of Biomedical Informatics 2024, 157: 104705. PMID: 39134233, DOI: 10.1016/j.jbi.2024.104705.Peer-Reviewed Original ResearchAlzheimer's Disease Genetics ConsortiumChart reviewPRS modelCase-control datasetGenetic association analysisGenetics ConsortiumPhenotype misclassificationSimulated phenotypesPhenotypic dataAssociation analysisEstimation of associated parametersBias reduction methodMedian thresholdPhenotypeMisclassification rateOriginal phenotypeDiverse arrayChartsMisclassificationGenotypesReviewEffects of biasBiasPrediction modelPRSLeveraging error-prone algorithm-derived phenotypes: Enhancing association studies for risk factors in EHR data
Lu Y, Tong J, Chubak J, Lumley T, Hubbard R, Xu H, Chen Y. Leveraging error-prone algorithm-derived phenotypes: Enhancing association studies for risk factors in EHR data. Journal Of Biomedical Informatics 2024, 157: 104690. PMID: 39004110, DOI: 10.1016/j.jbi.2024.104690.Peer-Reviewed Original ResearchElectronic health recordsElectronic health record dataKaiser Permanente WashingtonEHR-derived phenotypesAssociation studiesHealth recordsColon cancer recurrencePhenotyping errorsComputable phenotypeRisk factorsCancer recurrenceMultiple phenotypesReduce biasImprove estimation accuracySimulation studyBias reductionKaiserReduction of biasBiasEstimation accuracyAssociationStudyOutcomesRiskEstimation efficiency
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