Predicting symptomatic cerebral vasospasm after aneurysmal subarachnoid hemorrhage with an artificial neural network in a pediatric population.

Journal: Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery
Published Date: Dec 1, 2017

Abstract

PURPOSE: Artificial neural networks (ANN) are increasingly applied to complex medical problem solving algorithms because their outcome prediction performance is superior to existing multiple regression models. ANN can successfully identify symptomatic cerebral vasospasm (SCV) in adults presenting after aneurysmal subarachnoid hemorrhage (aSAH). Although SCV is unusual in children with aSAH, the clinical consequences are severe. Consequently, reliable tools to predict patients at greatest risk for SCV may have significant value. We applied ANN modeling to a consecutive cohort of pediatric aSAH cases to assess its ability to predict SCV.

Authors

  • Jesse Skoch
    Division of Neurosurgery, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave, Cincinnati, OH, 45229, USA.
  • Rizwan Tahir
    Department of Neurosurgery, Henry Ford Hospital, 2799 West Grand Blvd, Detroit, MI, 48202, USA.
  • Todd Abruzzo
    Department of Neurosurgery, University of Cincinnati College of Medicine, 231 Albert Sabin Way, Cincinnati, OH, 45267, USA.
  • John M Taylor
    Division of Neurology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave, Cincinnati, OH, 45229, USA.
  • Mario Zuccarello
    Department of Neurosurgery, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States.
  • Sudhakar Vadivelu
    Division of Neurosurgery, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave, Cincinnati, OH, 45229, USA. sudhakar.vadivelu@cchmc.org.

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