State of the Art of Artificial Intelligence in Clinical Electrophysiology in 2025: A Scientific Statement of the European Heart Rhythm Association (EHRA) of the ESC, the Heart Rhythm Society (HRS), and the ESC Working Group on E-Cardiology.

Journal: Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
Published Date:

Abstract

AIMS: Artificial intelligence (AI) has the potential to transform cardiac electrophysiology (EP), particularly in arrhythmia detection, procedural optimization, and patient outcome prediction. However, a standardized approach to reporting and understanding AI-related research in EP is lacking. This scientific statement aims to develop and apply a checklist for AI-related research reporting in EP to enhance transparency, reproducibility, and understandability in the field.

Authors

  • Emma Svennberg
    Department of MedicineKarolinska Institutet 171 77 Stockholm Sweden.
  • Janet K Han
    Division of Cardiology, VA Greater Los Angeles Healthcare System, Los Angeles, California. Electronic address: janet.han@va.gov.
  • Enrico G Caiani
    Department of Electronics, Information and Biomedical Engineering, Politecnico Di Milano, P.zza L. da Vinci 32, 20133, Milan, Italy. enrico.caiani@polimi.it.
  • Sandy Engelhardt
  • Sabine Ernst
    Department of Cardiology, Royal Brompton and Harefield NHS Foundation Trust, Sydney Street, London SW3 6NP, UK.
  • Paul Friedman
    Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA.
  • Rodrigue Garcia
    Cardiology Department, University Hospital of Poitiers, Poitiers, France.
  • Hamid Ghanbari
  • Gerhard Hindricks
    Department of Electrophysiology, Heart Center Leipzig at University of Leipzig, Strümpellstr. 39, 04289 Leipzig, Germany.
  • Sharon H Man
    Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom.
  • Jose Millet
  • Sanjiv M Narayan
    Biomedical Informatics Training Program (L.H., S.M.N.), Stanford University, CA.
  • G Andre Ng
  • Peter A Noseworthy
    Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota.
  • Fleur V Y Tjong
    Department of Cardiology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
  • Julia Ramírez
    Centro de Investigación Biomédica en Red, Biomateriales, Bioingeniería y Nanomedicina, Zaragoza, Spain.
  • Jagmeet P Singh
    Division of Cardiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Natalia Trayanova
    Department of Biomedical Engineering (A.P., N.T.).
  • David Duncker
    Hannover Heart Rhythm Center, Department of Cardiology and Angiology, Hannover Medical School, Hannover, Germany.
  • Jacob Tfelt Hansen
    Section of genetics, Department of Forensic Medicine, Faculty of Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
  • Joseph Barker
  • Ruben Casado-Arroyo
    Department of Cardiology, H.U.B.-Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium.
  • Neal A Chatterjee
    Division of Cardiology, Department of Medicine, University of Washington, Seattle, Washington, United States of America.
  • Giulio Conte
    Division of Cardiology, Fondazione Cardiocentro Ticino, Via Tesserete 48, Lugano 6900, Switzerland; Centre for Computational Medicine in Cardiology, Faculty of Informatics, Università della Svizzera Italiana, Via la Santa 1, Lugano 6900, Switzerland.
  • Søren Zöga Diederichsen
    Department of Cardiology, University Hospital Copenhagen-Rigshospitalet Copenhagen, Copenhagen, Denmark.
  • Dominik Linz
    Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark. dominik.linz@gmx.de.
  • Arun Umesh Mahtani
  • Alessandro Zorzi
    Department of Cardiac, Thoracic and Vascular Sciences and Public Health, University of Padua, Padua, Italy.