Artificial Intelligence and Transcatheter Interventions for Structural Heart Disease: A glance at the (near) future

Joana Maria Ribeiro, Patricio Astudillo, Ole de Backer, Ricardo Budde, Rutger Jan Nuis, Jeanette Goudzwaard, Nicolas M Van Mieghem, Joost Lumens, Peter Mortier, Francesco Mattace-Raso, Eric Boersma, Paul Cummins, Nico Bruining, Peter Pt de Jaegere*

*Corresponding author for this work

Research output: Contribution to journal(Systematic) Review article peer-review

Abstract

With innovations in therapeutic technologies and changes in population demographics, transcatheter interventions for structural heart disease have become the preferred treatment and will keep growing. Yet, a thorough clinical selection and efficient pathway from diagnosis to treatment and follow-up are mandatory. In this review we reflect on how artificial intelligence may help to improve patient selection, pre-procedural planning, procedure execution and follow-up so to establish efficient and high quality health care in an increasing number of patients.

Original languageEnglish
Pages (from-to)153-159
Number of pages7
JournalTrends in Cardiovascular Medicine
Volume32
Issue number3
Early online date10 Feb 2021
DOIs
Publication statusPublished - Apr 2022

Keywords

  • Artificial Intelligence
  • Machine Learning
  • Deep Learning
  • Transcatheter Interventions
  • Structural Heart Disease
  • COMPUTER-SIMULATION
  • ATRIAL-FIBRILLATION
  • VALVE
  • SEGMENTATION
  • PREDICTION
  • SURGERY
  • CT
  • REGURGITATION
  • ASSOCIATION
  • CARDIOLOGY

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