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

Child's Nervous System

Volumn 32, Issue 11, 2016, Pages 2143-2151

  Habibi, Zohreh ^a   Ertiaei, Abolhasan ^b   Nikdad, Mohammad Sadegh ^a   Mirmohseni, Atefeh Sadat ^a   Afarideh, Mohsen ^a   Heidari, Vahid ^a   Saberi, Hooshang ^b   Rezaei, Abdolreza Sheikh ^b   Nejat, Farideh ^a  

^a TEHRAN UNIVERSITY OF MEDICAL SCIENCES   (Iran)

^b TEHRAN UNIVERSITY OF MEDICAL SCIENCES   (Iran)

Author keywords

Artificial neural network; Hydrocephalus; Shunt infection; Ventriculoperitoneal shunt

Indexed keywords

ARTICLE; ARTIFICIAL NEURAL NETWORK; BIRTH WEIGHT; BRAIN HEMORRHAGE; BRAIN VENTRICLE PERITONEUM SHUNT; CHILD; CHILDHOOD DISEASE; CONTROLLED STUDY; FEMALE; FOLLOW UP; HUMAN; HYDROCEPHALUS; INFANT; LOW BIRTH WEIGHT; MAJOR CLINICAL STUDY; MALE; MEDICAL HISTORY; MENINGOMYELOCELE; MIXED INFECTION; NEWBORN; PREMATURITY; PRIORITY JOURNAL; RISK FACTOR; SHUNT INFECTION; ADVERSE EFFECTS; PRESCHOOL CHILD; SURGICAL WOUND INFECTION;

CHILD; CHILD, PRESCHOOL; FEMALE; HUMANS; HYDROCEPHALUS; INFANT; INFANT, NEWBORN; MALE; NEURAL NETWORKS (COMPUTER); RISK FACTORS; SURGICAL WOUND INFECTION; VENTRICULOPERITONEAL SHUNT;

EID: 84987673594     PISSN: 02567040     EISSN: 14330350     Source Type: Journal    
DOI: 10.1007/s00381-016-3248-2     Document Type: Article

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