Predicting central line-associated bloodstream infections and mortality using supervised machine learning.

Journal: Journal of critical care
PMID: 29486341

Abstract

PURPOSE: The purpose of this study was to compare machine learning techniques for predicting central line-associated bloodstream infection (CLABSI).

Authors

  • Joshua P Parreco
    Department of Surgery, University of Miami Miller School of Medicine, USA.
  • Antonio E Hidalgo
    Department of Surgery, University of Miami Miller School of Medicine, USA.
  • Alejandro D Badilla
    Division of Trauma Surgery and Surgical Critical Care, Department of Surgery, University of Miami Miller School of Medicine, USA.
  • Omar Ilyas
    Department of Internal Medicine, University of Miami Miller School of Medicine, USA.
  • Rishi Rattan
    Division of Trauma Surgery and Surgical Critical Care, Department of Surgery, University of Miami Miller School of Medicine, USA. Electronic address: rrattan@miami.edu.

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