Deep learning for electrocardiogram interpretation: Bench to bedside.

Journal: European journal of clinical investigation
PMID: 40191935

Abstract

BACKGROUND: Recent advancements in deep learning (DL), a subset of artificial intelligence, have shown the potential to automate and improve disease recognition, phenotyping and prediction of disease onset and outcomes by analysing various sources of medical data. The electrocardiogram (ECG) is a valuable tool for diagnosing and monitoring cardiovascular conditions.

Authors

  • Bas B S Schots
    Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Camila S Pizarro
    Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Bauke K O Arends
    Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Marish I F J Oerlemans
    Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Dino Ahmetagić
    Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Pim van der Harst
    Department of Cardiology, University Medical Center Utrecht, Heidelberglaan 100, Utrecht 3584 CX, The Netherlands.
  • René van Es
    Department of Cardiology, University Medical Center Utrecht, Heidelberglaan 100, Utrecht 3584 CX, The Netherlands.

Keywords

External Resources

Popular Topics
Recent Journals