Machine learning prediction of unexpected readmission or death after discharge from intensive care: A retrospective cohort study.

Journal: Journal of clinical anesthesia
PMID: 39405923

Abstract

BACKGROUND: Intensive care units (ICUs) harbor the sickest patients with the utmost needs of medical care. Discharge from ICU needs to consider the reason for admission and stability after ICU care. Organ dysfunction or instability after ICU discharge constitute potentially life-threatening situations for patients.

Authors

  • Thomas Tschoellitsch
    Department of Anesthesiology and Critical Care Medicine, Kepler University Hospital GmbH and Johannes Kepler University, Linz, Austria.
  • Alexander Maletzky
    Research Unit Medical Informatics, RISC Software GmbH, Hagenberg i. M., Austria. Electronic address: alexander.maletzky@risc-software.at.
  • Philipp Moser
    Research Unit Medical Informatics, RISC Software GmbH, Softwarepark 32a, Hagenberg, 4232, Austria. philipp.moser@risc-software.at.
  • Philipp Seidl
    European Laboratory for Learning and Intelligent Systems Unit Linz, Linz Institute of Technology Artificial Intelligence Lab, Institute for Machine Learning, Johannes Kepler University, Linz, Austria. Electronic address: seidl@ml.jku.at.
  • Carl Böck
    Department of Anesthesiology and Critical Care Medicine, Kepler University Hospital GmbH and Johannes Kepler University, Linz, Austria.
  • Tina Tomic Mahečić
    Clinic of Anaesthesiology and Intensive Care Medicine, University Hospital Centre Zagreb - Rebro, Croatia. Electronic address: ttomic@kbc-zagreb.hr.
  • Stefan Thumfart
    Research Unit Medical Informatics, RISC Software GmbH, Softwarepark 32a, Hagenberg, 4232, Austria.
  • Michael Giretzlehner
    Research Unit Medical Informatics, RISC Software GmbH, Hagenberg i. M., Austria. Electronic address: michael.giretzlehner@risc-software.at.
  • Sepp Hochreiter
    Institute for Machine Learning Johannes Kepler University Linz Austria.
  • Jens Meier
    Department of Anesthesiology and Intensive Care Medicine, Faculty of Medicine of the Kepler University Linz, Krankenhausstraße 9, 4020 Linz, Austria. Electronic address: jens.meier@gmail.com.

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