Electrocardiographic diagnostic possibilities for atrial fibrillation using artificial intelligence: Differentiation from sinus rhythm and other arrhythmias with the PMcardio app in COVID-19 patients.

Journal: Journal of electrocardiology
Published Date: May 10, 2025

Abstract

BACKGROUND: Artificial intelligence (AI) has shown potential in enhancing ECG analysis, but its accuracy in detecting atrial fibrillation (AF) in COVID-19 patients remains unstudied. Given the increased risk of arrhythmias and thromboembolic events in this population, AI could aid in timely correct diagnosis, reduce unnecessary consultations, tests, and minimize infection spread. This study evaluated the diagnostic performance of the AI-based PMcardio application in detecting AF in COVID-19 patients.

Authors

  • Rita Vainoryte
    Faculty of Medicine, Medical Academy, Lithuanian University of Health Sciences, A. Mickevičiaus str. 9, LT-44307 Kaunas, Lithuania. Electronic address: rita.vainoryte@stud.lsmu.lt.
  • Jonas Jucevicius
    Department of Internal Medicine, Faculty of Medicine, Medical Academy, Lithuanian University of Health Sciences, Josvainių str. 2, LT-47144 Kaunas, Lithuania.
  • Edis Baubonis
    Faculty of Medicine, Medical Academy, Lithuanian University of Health Sciences, A. Mickevičiaus str. 9, LT-44307 Kaunas, Lithuania.
  • Albinas Naudžiūnas
    Lithuanian University of Health Sciences, Kaunas, Lithuania.
  • Andrius Alisauskas
    Department of Internal Medicine, Faculty of Medicine, Medical Academy, Lithuanian University of Health Sciences, Josvainių str. 2, LT-47144 Kaunas, Lithuania.
  • Egle Kalinauskiene
    Department of Internal Medicine, Faculty of Medicine, Medical Academy, Lithuanian University of Health Sciences, Josvainių str. 2, LT-47144 Kaunas, Lithuania.

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