title: [The study on the early diagnosis of hypoxic ischemic encephalopathy (HIE) in the newborns by fuzzy BP neural networks].
abstract: This paper is aimed to study a method and feasibility of early diagnostic system using hypoxic ischemic encephalopathy (HIE) in the newborns. Fifteen non-invasive indicators with high sensitivity and specificity were selected for the early diagnosis of HIE on the basis of related researches from the literature and the researches in our laboratory. The diagnostic test was done with 140 cases with the HIE, using the fussy BP neural network experiment system. The initial results showed that the accuracy rate was 100% for the training set and 95% for the testing set, and the error rate was 5%. The data suggested that the fuzzy back-propagation neural networks, with the clinical comprehensive indicators, exhibited a high accuracy for the early diagnosis of HIE. This method provides an objective and convenient new way for the early clinical diagnosis of the HIE.
authors.affiliation: First Affiliated Hospital, Medical College of Xi'an Jiaotong University, Xi'an 710061, China. nellie918@yahoo.com.cn
authors.forename: Li
authors.initials: L
authors.lastname: Liu
authors.forename: Liqin
authors.initials: L
authors.lastname: Huo
authors.forename: Feng
authors.initials: F
authors.lastname: Zhang
authors.forename: Chongxun
authors.initials: C
authors.lastname: Zheng
authors.forename: Jia
authors.initials: J
authors.lastname: You
authors.forename: Xining
authors.initials: X
authors.lastname: He
authors.forename: Jie
authors.initials: J
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D042241:Early Diagnosis; D005260:Female; D017143:Fuzzy Logic; D006801:Humans; D020925:Hypoxia-Ischemia, Brain / Q000175:diagnosis*; D007231:Infant, Newborn; D008297:Male; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity