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Explainable Boosting Machine approach identifies risk factors for acute renal failure.

Andreas KörnerBenjamin SailerSibel Sari-YavuzHelene A HaeberleValbona MirakajAlice BernardPeter RosenbergerMichael Koeppen
Published in: Intensive care medicine experimental (2024)
Using an Explainable Boosting Machine enhance the precision in AKI risk factors in ICU patients, providing a more nuanced understanding of known AKI risks. This approach allows for refined predictive modeling of AKI, effectively overcoming the limitations of traditional statistical models.
Keyphrases
  • acute kidney injury
  • risk factors
  • end stage renal disease
  • ejection fraction
  • newly diagnosed
  • deep learning
  • chronic kidney disease
  • liver failure
  • intensive care unit
  • peritoneal dialysis
  • genome wide
  • climate change