Chenxi Huang
Associate Research ScientistDownloadHi-Res Photo
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Cardiovascular Medicine
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Associate Research Scientist
Biography
Chenxi Huang finished her PhD program in Biomedical Engineering at Yale University in 2015. Her PhD thesis focuses on dealing with outliers in cryo-EM reconstruction of large molecules. Her research interests are fundamental issues of and innovative mathematical and computational approaches to biomedical data analysis, identification and integration of critical information in and across various imaging modalities, and sparse representations in detection and estimation for massive high-dimensional and noisy data. Prior to her PhD, she received her bachelor degree in Information Engineering from Shanghai Jiaotong University and Master of Science in Electrical Engineering from Yale University.
Appointments
Cardiovascular Medicine
Associate Research ScientistPrimary
Other Departments & Organizations
- Cardiovascular Medicine
- Center for Outcomes Research & Evaluation (CORE)
- Internal Medicine
Research
Research at a Glance
Yale Co-Authors
Frequent collaborators of Chenxi Huang's published research.
Publications Timeline
A big-picture view of Chenxi Huang's research output by year.
Harlan Krumholz, MD, SM
Yuan Lu, ScD
Mitsuaki Sawano, MD, PhD
Rohan Khera, MD, MS
Akiko Iwasaki, PhD
Bornali Bhattacharjee
15Publications
39Citations
Publications
2024
Use of electronic health records to characterize patients with uncontrolled hypertension in two large health system networks
Lu Y, Keeley E, Barrette E, Cooper-DeHoff R, Dhruva S, Gaffney J, Gamble G, Handke B, Huang C, Krumholz H, McDonough C, Schulz W, Shaw K, Smith M, Woodard J, Young P, Ervin K, Ross J. Use of electronic health records to characterize patients with uncontrolled hypertension in two large health system networks. BMC Cardiovascular Disorders 2024, 24: 497. PMID: 39289597, PMCID: PMC11409735, DOI: 10.1186/s12872-024-04161-x.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsConceptsElectronic health recordsHealth recordsHealth systemUncontrolled hypertensionUse of electronic health recordsHypertension managementElectronic health record systemsOneFlorida Clinical Research ConsortiumElectronic health record dataYale New Haven Health SystemBP measurementsICD-10-CM codesHealth system networkPublic health priorityICD-10-CMIncidence rate of deathElevated BP measurementsElevated blood pressure measurementsHealthcare visitsAmbulatory careHealth priorityRetrospective cohort studyEHR dataOneFloridaBlood pressure measurementsInternal tremors and vibrations in long COVID: a cross-sectional study
Zhou T, Sawano M, Arun A, Caraballo C, Michelsen T, McAlpine L, Bhattacharjee B, Lu Y, Khera R, Huang C, Warner F, Herrin J, Iwasaki A, Krumholz H. Internal tremors and vibrations in long COVID: a cross-sectional study. The American Journal Of Medicine 2024 PMID: 39069199, DOI: 10.1016/j.amjmed.2024.07.008.Peer-Reviewed Original ResearchCitationsAltmetricConceptsNew-onset conditionsInternal tremorLong COVID symptomsCOVID symptomsNon-Hispanic whitesCross-sectional studyQuality of lifeVisual analogue scaleWorse healthHealth statusStudy participantsDemographic characteristicsAnalogue scaleOutcome variablesNeurological conditionsLong COVIDMast cell disordersTreatment experienceHealthComorbiditiesSymptomsMedian agePeopleCell disordersLong COVID Characteristics and Experience: A Descriptive Study from the Yale LISTEN Research Cohort
Sawano M, Wu Y, Shah R, Zhou T, Arun A, Khosla P, Kaleem S, Vashist A, Bhattacharjee B, Ding Q, Lu Y, Caraballo C, Warner F, Huang C, Herrin J, Putrino D, Michelsen T, Fisher L, Adinig C, Iwasaki A, Krumholz H. Long COVID Characteristics and Experience: A Descriptive Study from the Yale LISTEN Research Cohort. The American Journal Of Medicine 2024 PMID: 38663793, DOI: 10.1016/j.amjmed.2024.04.015.Peer-Reviewed Original ResearchCitationsAltmetricConceptsExperiences of peopleHealth statusLong COVIDLower health statusNew-onset conditionsCommunity support servicesNon-Hispanic whitesArray of healthQuality of lifeVisual analogue scaleMental healthPsychological distressPsychological statusDescriptive studyHealthcare systemMedian scoreSupport servicesResearch cohortSocial isolationDemographic characteristicsAnalogue scaleImpact of long COVIDHealthFinancial stressParticipantsHeterogeneity in the Prognosis of Acute Kidney Injury Following Percutaneous Coronary Intervention
Hu J, Murugiah K, Xin X, Sawano M, Lu Y, Wilson F, Masoudi F, Messenger J, Krumholz H, Huang C. Heterogeneity in the Prognosis of Acute Kidney Injury Following Percutaneous Coronary Intervention. Journal Of The American Heart Association 2024, 13: e033649. PMID: 38390832, PMCID: PMC10944032, DOI: 10.1161/jaha.123.033649.Peer-Reviewed Original ResearchAltmetric
2023
Effect of the New Glomerular Filtration Rate Estimation Equation on Risk Predicting Models for Acute Kidney Injury After Percutaneous Coronary Intervention
Huang C, Murugiah K, Li X, Masoudi F, Messenger J, Williams K, Mortazavi B, Krumholz H. Effect of the New Glomerular Filtration Rate Estimation Equation on Risk Predicting Models for Acute Kidney Injury After Percutaneous Coronary Intervention. Circulation Cardiovascular Interventions 2023, 16: e012831. PMID: 37009734, PMCID: PMC10622038, DOI: 10.1161/circinterventions.122.012831.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsNonexercise machine learning models for maximal oxygen uptake prediction in national population surveys.
Liu Y, Herrin J, Huang C, Khera R, Dhingra L, Dong W, Mortazavi B, Krumholz H, Lu Y. Nonexercise machine learning models for maximal oxygen uptake prediction in national population surveys. Journal Of The American Medical Informatics Association 2023, 30: 943-952. PMID: 36905605, PMCID: PMC10114129, DOI: 10.1093/jamia/ocad035.Peer-Reviewed Original ResearchCitationsAltmetricQuantifying Blood Pressure Visit-to-Visit Variability in the Real-World Setting: A Retrospective Cohort Study
Lu Y, Linderman G, Mahajan S, Liu Y, Huang C, Khera R, Mortazavi B, Spatz E, Krumholz H. Quantifying Blood Pressure Visit-to-Visit Variability in the Real-World Setting: A Retrospective Cohort Study. Circulation Cardiovascular Quality And Outcomes 2023, 16: e009258. PMID: 36883456, DOI: 10.1161/circoutcomes.122.009258.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsRetrospective cohort studyBlood pressure valuesPatient characteristicsReal-world settingCohort studyPatient subgroupsYale New Haven Health SystemMean body mass indexSystolic blood pressure valuesBlood pressure visitHistory of hypertensionCoronary artery diseaseManagement of patientsMultivariable linear regression modelsBlood pressure readingsBody mass indexPatient-level measuresBlood pressure variationAbsolute standardized differencesNon-Hispanic whitesAntihypertensive medicationsReal-world practiceVisit variabilityArtery diseaseRegression models
2021
A Simple Recovery Framework for Signals with Time-Varying Sparse Support
Durgin N, Grotheer R, Huang C, Li S, Ma A, Needell D, Qin J. A Simple Recovery Framework for Signals with Time-Varying Sparse Support. Association For Women In Mathematics Series 2021, 26: 211-230. DOI: 10.1007/978-3-030-79891-8_9.Peer-Reviewed Original ResearchStochastic greedy algorithms for multiple measurement vectors
Qin J, Li S, Needell D, Ma A, Grotheer R, Huang C, Durgin N. Stochastic greedy algorithms for multiple measurement vectors. Inverse Problems And Imaging 2021, 15: 79-107. DOI: 10.3934/ipi.2020066.Peer-Reviewed Original ResearchCitations
2019
Jointly Sparse Signal Recovery with Prior Info
Durgin N, Grotheer R, Huang C, Li S, Ma A, Needell D, Qin J. Jointly Sparse Signal Recovery with Prior Info. 2019, 00: 645-649. DOI: 10.1109/ieeeconf44664.2019.9048818.Peer-Reviewed Original ResearchCitations