The Development and Validation of a Machine Learning Model to Predict Bacteremia and Fungemia in Hospitalized Patients Using Electronic Health Record Data.

Journal: Critical care medicine
PMID: 32796184

Abstract

OBJECTIVES: Bacteremia and fungemia can cause life-threatening illness with high mortality rates, which increase with delays in antimicrobial therapy. The objective of this study is to develop machine learning models to predict blood culture results at the time of the blood culture order using routine data in the electronic health record.

Authors

  • Sivasubramanium V Bhavani
    Department of Medicine, University of Chicago Medical Center, Chicago, IL.
  • Zachary Lonjers
    Department of Medicine, Northshore Hospital, Chicago, IL.
  • Kyle A Carey
    Department of Medicine, University of Chicago, Chicago IL, United States.
  • Majid Afshar
    Loyola University Chicago, Chicago, IL.
  • Emily R Gilbert
    Department of Medicine, Loyola University Medical Center, Maywood, Illinois.
  • Nirav S Shah
    Department of Medicine, Northshore Hospital, Chicago, IL.
  • Elbert S Huang
    Department of Medicine, University of Chicago Medical Center, Chicago, IL.
  • Matthew M Churpek
    Department of Medicine, University of Wisconsin-Madison, Madison, WI, United States.

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