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Machine learning-based analysis of non-invasive measurements for predicting intracardiac pressures.

Annemiek E van RavensbergNiels T B ScholteAaram Omar KhaderJasper J BrugtsNico BruiningRobert M A van der Boon
Published in: European heart journal. Digital health (2024)
In this study, non-invasive methods, both traditional and ML-based, showed limited correlation to PCWP. This highlights the weak correlation between traditional HF monitoring and haemodynamic parameters, also emphasizing the limitations of single non-invasive measurements. Future research should explore trend analysis and additional features to improve non-invasive haemodynamic monitoring, as there is a clear demand for further advancements in this field.
Keyphrases
  • machine learning
  • artificial intelligence
  • heart failure
  • left atrial appendage
  • deep learning
  • atrial fibrillation