Predicting ventriculoperitoneal shunt infection in children with hydrocephalus using artificial neural network.

Journal: Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery
Published Date: Nov 1, 2016

Abstract

OBJECTIVES: The relationships between shunt infection and predictive factors have not been previously investigated using Artificial Neural Network (ANN) model. The aim of this study was to develop an ANN model to predict shunt infection in a group of children with shunted hydrocephalus.

Authors

  • Zohreh Habibi
    Department of Neurosurgery, Children's Hospital Medical Center, Tehran University of Medical Science, Gharib street, Tehran, 141557854, Iran.
  • Abolhasan Ertiaei
    Department of Neurosurgery, Imam Khomeini Hospital, Tehran University of Medical Science, Tehran, Iran.
  • Mohammad Sadegh Nikdad
    Department of Neurosurgery, Children's Hospital Medical Center, Tehran University of Medical Science, Gharib street, Tehran, 141557854, Iran.
  • Atefeh Sadat Mirmohseni
    Department of Neurosurgery, Children's Hospital Medical Center, Tehran University of Medical Science, Gharib street, Tehran, 141557854, Iran.
  • Mohsen Afarideh
    Department of Neurosurgery, Children's Hospital Medical Center, Tehran University of Medical Science, Gharib street, Tehran, 141557854, Iran.
  • Vahid Heidari
    Department of Neurosurgery, Children's Hospital Medical Center, Tehran University of Medical Science, Gharib street, Tehran, 141557854, Iran.
  • Hooshang Saberi
    Department of Neurosurgery, Imam Khomeini Hospital, Tehran University of Medical Science, Tehran, Iran.
  • Abdolreza Sheikh Rezaei
    Department of Neurosurgery, Imam Khomeini Hospital, Tehran University of Medical Science, Tehran, Iran.
  • Farideh Nejat
    Department of Neurosurgery, Children's Hospital Medical Center, Tehran University of Medical Science, Gharib street, Tehran, 141557854, Iran. nejat@sina.tums.ac.ir.

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