Application of machine learning to the prediction of postoperative sepsis after appendectomy.

Journal: Surgery
PMID:

Abstract

BACKGROUND: We applied various machine learning algorithms to a large national dataset to model the risk of postoperative sepsis after appendectomy to evaluate utility of such methods and identify factors associated with postoperative sepsis in these patients.

Authors

  • Corinne Bunn
    Department of Surgery, Loyola University Medical Center, Maywood, IL; Burn Shock Trauma Research Institute, Loyola University Chicago, Maywood, IL.
  • Sujay Kulshrestha
    Department of Surgery, Loyola University Medical Center, Maywood, IL; Burn Shock Trauma Research Institute, Loyola University Chicago, Maywood, IL.
  • Jason Boyda
    Informatics and Systems Development, Health Sciences Division, Loyola University Chicago, Maywood, Illinois, USA.
  • Neelam Balasubramanian
    Informatics and Systems Development, Health Sciences Division, Loyola University Chicago, Maywood IL.
  • Steven Birch
    Informatics and Systems Development, Health Sciences Division, Loyola University Chicago, Maywood, Illinois, USA.
  • Ibrahim Karabayir
    Center for Health Outcomes and Informatics Research, Health Sciences Division, Loyola University Chicago, Maywood, IL; Department of Health Informatics and Data Science, Loyola University Chicago, Chicago, IL; Kirklareli University, Kirklareli, Turkey.
  • Marshall Baker
    Department of Surgery, Loyola University Medical Center, Maywood, IL; Edward Hines, Jr Veterans Administration Hospital, Hines, IL.
  • Fred Luchette
    Department of Surgery, Loyola University Medical Center, Maywood, IL; Edward Hines, Jr Veterans Administration Hospital, Hines, IL.
  • François Modave
    Health Outcomes & Biomedical Informatics, College of Medicine, University of Florida, 2004 Mowry Road, Gainesville, FL, 32610, USA.
  • Oguz Akbilgic
    1Department of Pediatrics, University of Tennessee Health Science Center - Oak Ridge National Laboratory- (UTHSC-ORNL), Center for Biomedical Informatics, Memphis, TN USA.