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Jessica K. Zègre‐Hemsey

Electrophysiology
University of North Carolina at Chapel Hill

About

Jessica K. Zègre‐Hemsey works in Electrophysiology affiliated with University of North Carolina at Chapel Hill.

Jessica K. Zègre-Hemsey is an associate professor at the University of North Carolina at Chapel Hill School of Nursing. She holds an adjunct faculty appointment in the Department of Emergency Medicine at the UNC School of Medicine. Her research focuses on improving outcomes for individuals with acute coronary syndrome and other time-sensitive cardiovascular conditions through cardiac monitoring and evidence-based innovations in prehospital care.

Research focus

ECG monitoring and analysisCardiac arrest resuscitationAcute myocardial infarction diagnosisPrehospital emergency cardiac careMachine learning for ECG risk stratification

Impact

139 pubs · 2,162 cites · h-index 25

Affiliations

Publications

Recent publications by Jessica K. Zègre‐Hemsey

  1. Fusion of ECG Foundation Model Embeddings to Improve Early Detection of Acute Coronary SyndromesSun,
  2. Treatment Times and In-Hospital Mortality Among Patients with ST-Elevation Myocardial Infarction Throughout the Waves of the COVID-19 Pandemic: Lessons LearnedCOVID · Fri,
  3. Adversarial Debiasing for Equitable and Fair Detection of Acute Coronary Syndrome using 12-Lead ECGIEEE Transactions on Biomedical Engineering · Wed,
  4. Fusion of ECG Foundation Model Embeddings to Improve Early Detection of Acute Coronary Syndromes.Thu,
  5. Electrocardiogram-based machine learning for risk stratification of patients with suspected acute coronary syndromeEuropean Heart Journal · Mon,
  6. Clinical usability of deep learning-based saliency maps for occlusion myocardial infarction identification from the prehospital 12-Lead electrocardiogramJournal of Electrocardiology · Mon,
  7. AI and Social Determinants of Health in Health Care: A Personal PerspectiveNorth Carolina Medical Journal · Thu,
  8. Selective classification with machine learning uncertainty estimates improves ACS prediction: A retrospective study in the prehospital setting. Wed,
  9. ECG-SMART-NET: A Deep Learning Architecture for Precise ECG Diagnosis of Occlusion Myocardial InfarctionWed,
  10. Pandemic effect on ischaemic burden and prehospital time in acute coronary syndromeInternational Paramedic Practice · Tue,