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Monitoring left ventricular assist device parameters to detect flow- and power-impacting complications: a proof of concept.

Mehran MoazeniLieke NumanMariusz K SzymanskiNiels P van der KaaijFolkert W. AsselbergsLinda W Van LaakeEmmeke Aarts
Published in: European heart journal. Digital health (2023)
The proposed algorithm showed that the personalized algorithm is a viable approach to early identify cardiac arrhythmia and major bleeding by monitoring HM3 pump parameters. External validation is needed and integration with other clinical parameters could potentially improve the predictive value. In addition, the algorithm can be further enhanced using continuous data.
Keyphrases
  • left ventricular assist device
  • machine learning
  • deep learning
  • neural network
  • big data
  • electronic health record
  • atrial fibrillation
  • left ventricular
  • risk factors
  • heart failure
  • data analysis