2024
Improving tabular data extraction in scanned laboratory reports using deep learning models
Li Y, Wei Q, Chen X, Li J, Tao C, Xu H. Improving tabular data extraction in scanned laboratory reports using deep learning models. Journal Of Biomedical Informatics 2024, 159: 104735. PMID: 39393477, DOI: 10.1016/j.jbi.2024.104735.Peer-Reviewed Original ResearchTree edit distanceOptical character recognitionTable recognitionDeep learning modelsAverage recallAverage precisionState-of-the-art deep learning modelsLearning modelsRegion-of-interest detectionState-of-the-artCharacter recognitionDetection evaluationTree editingTabular dataImpressive resultsLab test resultsLaboratory test reportsClinical documentationRecognitionLaboratory reportsHealthcare organizationsClinical data analysisDecision makingClinical decision makingTest reports
2020
Interference between rhinovirus and influenza A virus: a clinical data analysis and experimental infection study
Wu A, Mihaylova VT, Landry ML, Foxman EF. Interference between rhinovirus and influenza A virus: a clinical data analysis and experimental infection study. The Lancet Microbe 2020, 1: e254-e262. PMID: 33103132, PMCID: PMC7580833, DOI: 10.1016/s2666-5247(20)30114-2.Peer-Reviewed Original ResearchConceptsRhinovirus infectionInterferon-stimulated genesExperimental infection studiesClinical data analysisMock infectionInfection studiesDay 3ISG expressionViral interferenceInterferon responsePrimary human airway epithelial culturesYale-New Haven HospitalHuman airway epithelial culturesIAV RNASeasonal influenza epidemicsNational InstituteAirway epithelial culturesReverse transcription-quantitative PCRTranscription-quantitative PCRElectronic medical record systemPeak virusAirway mucosaMedical record systemRespiratory virusesIAV infection
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