Guannan Gong, PhD
Associate Research ScientistCards
About
Research
Publications
2026
Clinical Trial Patient Matching: A Real-Time, Common Data Model and Artificial Intelligence–Driven System for Semiautomated Patient Prescreening in Cancer Clinical Trials
Gong G, Liu J, Pandya S, Taborda C, Wiesendanger N, Price N, Byron W, Coppi A, Young P, Wiess C, Dunning H, Barganier C, Brodeur R, Fischbach N, LoRusso P, Pusztai L, Kim S, Rozenblit M, Cecchini M, Mongiu A, Mendez L, Kaftan E, Torre C, Krumholz H, Krop I, Schulz W, Lustberg M, Kunz P. Clinical Trial Patient Matching: A Real-Time, Common Data Model and Artificial Intelligence–Driven System for Semiautomated Patient Prescreening in Cancer Clinical Trials. JCO Clinical Cancer Informatics 2026, 10: e2500262. PMID: 41512229, DOI: 10.1200/cci-25-00262.Peer-Reviewed Original ResearchConceptsObservational Medical Outcomes PartnershipHealth systemColorectal cancerElectronic health record dataCancer clinical trial enrollmentChart reviewHealth record dataManual chart reviewClinical trial recruitmentClinical trialsCancer clinical trialsCancer specialtiesCommon data modelScreen timeColorectal cancer trialsClinical trial enrollmentTrial recruitmentClinical chart reviewConsent ratesPatient accessExhaustive chart reviewMetastatic colorectal cancerEnrollment challengesRecord dataTrial enrollmentAssessment of the integrity of real-time electronic health record data used in clinical research
Liu J, Pandya S, Coppi A, Young H, Krumholz H, Schulz W, Gong G. Assessment of the integrity of real-time electronic health record data used in clinical research. PLOS ONE 2026, 21: e0340287. PMID: 41511976, PMCID: PMC12788664, DOI: 10.1371/journal.pone.0340287.Peer-Reviewed Original ResearchConceptsElectronic health recordsEHR dataReal-time electronic health recordsElectronic health record dataSecondary useHealth record dataClinical actionsIntegration of real-time dataClinical trial readinessCommon data modelHealth recordsHealth systemOMOP Common Data ModelDischarge informationClinical careResearch readinessRecord dataTrial readinessSynthetic datasetsEHR datasetData warehouseDemographic variablesReal-time dataPost-encounterAutomated framework
2021
Clinical characteristics and outcomes for 7,995 patients with SARS-CoV-2 infection
McPadden J, Warner F, Young HP, Hurley NC, Pulk RA, Singh A, Durant TJS, Gong G, Desai N, Haimovich A, Taylor RA, Gunel M, Dela Cruz CS, Farhadian SF, Siner J, Villanueva M, Churchwell K, Hsiao A, Torre CJ, Velazquez EJ, Herbst RS, Iwasaki A, Ko AI, Mortazavi BJ, Krumholz HM, Schulz WL. Clinical characteristics and outcomes for 7,995 patients with SARS-CoV-2 infection. PLOS ONE 2021, 16: e0243291. PMID: 33788846, PMCID: PMC8011821, DOI: 10.1371/journal.pone.0243291.Peer-Reviewed Original ResearchConceptsSARS-CoV-2 infectionYale New Haven HealthSARS-CoV-2Hospital mortalityRisk of admissionMale sexRisk factorsSARS-CoV-2 testingInvasive mechanical ventilationSevere acute respiratory syndrome virusBurden of diseaseRT-PCR testingAcademic health systemDiverse patient populationsRespiratory syndrome virusEthnic groupsAdult patientsClinical characteristicsDischarge dispositionRespiratory supportPrimary outcomeTreatment guidelinesMechanical ventilationRetrospective studyPatient population
2020
Patient factors associated with SARS‐CoV‐2 in an admitted emergency department population
Haimovich A, Warner F, Young HP, Ravindra NG, Sehanobish A, Gong G, Wilson FP, van Dijk D, Schulz W, Taylor R. Patient factors associated with SARS‐CoV‐2 in an admitted emergency department population. Journal Of The American College Of Emergency Physicians Open 2020, 1: 569-577. PMID: 32838371, PMCID: PMC7280703, DOI: 10.1002/emp2.12145.Peer-Reviewed Original ResearchCOVID-19 positive patientsPatient characteristicsPatient factorsCOVID-19Positive COVID-19 testMultivariable logistic regression modelLow pulse oximetryChronic lung diseaseRetrospective observational studyCOVID-19 test resultsEmergency department patientsPrimary outcome measureEmergency department populationLower leukocyte countsPositive COVID-19 resultHistory of alcoholPositive test resultsSARS-CoV-2 virusSARS-CoV-2COVID-19 testingLogistic regression modelsCOVID-19 testCOVID-19 resultsED cohortNegative patientsBridging the Collaboration Gap: Real-time Identification of Clinical Specimens for Biomedical Research
Durant TJS, Gong G, Price N, Schulz WL. Bridging the Collaboration Gap: Real-time Identification of Clinical Specimens for Biomedical Research. Journal Of Pathology Informatics 2020, 11: 14. PMID: 32477620, PMCID: PMC7245342, DOI: 10.4103/jpi.jpi_15_20.Peer-Reviewed Original ResearchOpen source applicationsReal timeReal-time environmentDifferent use casesE-mail notificationData architectureUnstructured dataCommodity hardwareUse casesMinimal overheadReal-time identificationAdditional data typesData typesReal-world clinical dataCollaboration gapsClinical workflowSpecimen metadataTypical approachShort stability timeHealth platformNovel approachSpecimen retentionFuture workElasticsearchNotification
Academic Achievements & Community Involvement
News
News
- March 24, 2026
AI in Cancer Workshop: Advancing Precision Medicine through Interdisciplinary Innovation
- December 13, 2025
Yale research advances presented at San Antonio Breast Cancer Symposium annual meeting
- July 08, 2025Source: Yale Ventures
Eight Translational Biotech Projects Selected for 2025 Blavatnik Accelerator Awards
- June 12, 2024Source: Yale New Haven Health
Yale New Haven Health and Yale University celebrate Innovation Awards