Artificial Intelligence Advancements in Cardiomyopathies: Implications for Diagnosis and Management of Arrhythmogenic Cardiomyopathy.

Journal: Current heart failure reports
PMID: 39661213

Abstract

PURPOSE OF REVIEW: This review aims to explore the emerging potential of artificial intelligence (AI) in refining risk prediction, clinical diagnosis, and treatment stratification for cardiomyopathies, with a specific emphasis on arrhythmogenic cardiomyopathy (ACM).

Authors

  • Arman Salavati
    Department of Cardiology, Division Heart & Lungs, University Medical Centre Utrecht, University Utrecht, Utrecht, the Netherlands.
  • C Nina van der Wilt
    Department of Cardiology, Division Heart & Lungs, University Medical Centre Utrecht, University Utrecht, Utrecht, the Netherlands.
  • Martina Calore
    Department of Biology, University of Padua, Padua, Italy.
  • RenĂ© van Es
    Department of Cardiology, University Medical Center Utrecht, Heidelberglaan 100, Utrecht 3584 CX, The Netherlands.
  • Alessandra Rampazzo
    Department of Biology, University of Padua, Padua, Italy.
  • Pim van der Harst
    Department of Cardiology, University Medical Center Utrecht, Heidelberglaan 100, Utrecht 3584 CX, The Netherlands.
  • Frank G van Steenbeek
    Department of Cardiology, Division Heart & Lungs, University Medical Centre Utrecht, University Utrecht, Utrecht, the Netherlands.
  • J Peter van Tintelen
    University Medical Centre Utrecht.
  • Magdalena Harakalova
    Department of Cardiology, Division Heart & Lungs, University Medical Centre Utrecht, University Utrecht, Utrecht, the Netherlands.
  • Anneline S J M Te Riele
    Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands.

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