Prediction of incident atrial fibrillation using deep learning, clinical models, and polygenic scores.

Journal: European heart journal
PMID: 39217446

Abstract

BACKGROUND AND AIMS: Deep learning applied to electrocardiograms (ECG-AI) is an emerging approach for predicting atrial fibrillation or flutter (AF). This study introduces an ECG-AI model developed and tested at a tertiary cardiac centre, comparing its performance with clinical models and AF polygenic score (PGS).

Authors

  • Gilbert Jabbour
    Electrophysiology Service, Department of Medicine, Montreal Heart Institute, Université de Montréal, 5000 rue Bélanger, Montreal, QC H1T 1C8, Canada.
  • Alexis Nolin-Lapalme
    Department of Medicine, Montreal Heart Institute, Montreal, Quebec, Canada; Faculté de Médecine, Université de Montréal, Montreal, Quebec, Canada; Mila - Québec AI Institute, Montreal, Quebec, Canada; Heartwise (heartwise.ai), Montreal Heart Institute, Montreal, Quebec, Canada. Electronic address: alexis.nolin-lapalme@umontreal.ca.
  • Olivier Tastet
    Department of Medicine, Montreal Heart Institute, Montreal, Quebec, Canada.
  • Denis Corbin
    Laboratoire d'Imagerie optique et Moléculaire, Polytechnique Montréal, 2500 Chemin de Polytechnique Montréal, Montreal, QC, H3T 1J4, Canada. denis.corbin@hotmail.com.
  • Paloma Jordà
    Montreal Heart Institute Research Centre, 5000 Belanger St, Montreal, Quebec H1T 1C8, Canada.
  • Achille Sowa
    Montreal Heart Institute Research Centre, 5000 Belanger St, Montreal, Quebec H1T 1C8, Canada.
  • Jacques Delfrate
    Montreal Heart Institute Research Centre, 5000 Belanger St, Montreal, Quebec H1T 1C8, Canada.
  • David Busseuil
    Montreal Heart Institute Research Centre, 5000 Belanger St, Montreal, Quebec H1T 1C8, Canada.
  • Julie G Hussin
    Department of Medicine, Montreal Heart Institute, Montreal, Quebec, Canada; Faculté de Médecine, Université de Montréal, Montreal, Quebec, Canada; Mila - Québec AI Institute, Montreal, Quebec, Canada.
  • Marie-Pierre Dubé
    Montreal Heart Institute Research Centre, 5000 Belanger St, Montreal, Quebec H1T 1C8, Canada.
  • Jean-Claude Tardif
    Montreal Heart Institute, Université de Montréal, Montreal, QC.
  • Léna Rivard
    Montreal Heart Institute Research Centre, 5000 Belanger St, Montreal, Quebec H1T 1C8, Canada.
  • Laurent Macle
    Electrophysiology Service, Department of Medicine, Montreal Heart Institute, Université de Montréal, 5000 rue Bélanger, Montreal, QC H1T 1C8, Canada.
  • Julia Cadrin-Tourigny
    Montreal Heart Institute, Department of Medicine, Université de Montréal, Montreal, Quebec, Canada.
  • Paul Khairy
    Electrophysiology Service, Department of Medicine, Montreal Heart Institute, Université de Montréal, 5000 rue Bélanger, Montreal, QC H1T 1C8, Canada.
  • Robert Avram
    Division of Cardiology, Department of Medicine, Montreal Heart Institute, University of Montreal, Montreal, QC H1T 1C8, Canada. Electronic address: robert.avram.md@gmail.com.
  • Rafik Tadros
    Montreal Heart Institute, Department of Medicine, Université de Montréal, Montreal, Quebec, Canada.

Keywords

External Resources

Popular Topics
Recent Journals