The study on the early diagnosis of hypoxic ischemic encephalopathy (HIE) in the newborns by fuzzy BP neural networks.
- Author:
Li LIU
1
;
Liqin HUO
;
Feng ZHANG
;
Chongxun ZHENG
;
Jia YOU
;
Xining HE
;
Jie ZHANG
Author Information
1. First Affiliated Hospital, Medical College of Xi'an Jiaotong University, Xi'an 710061, China. nellie918@yahoo.com.cn
- Publication Type:Journal Article
- MeSH:
Algorithms;
Diagnosis, Computer-Assisted;
methods;
Early Diagnosis;
Female;
Fuzzy Logic;
Humans;
Hypoxia-Ischemia, Brain;
diagnosis;
Infant, Newborn;
Male;
Neural Networks (Computer);
Pattern Recognition, Automated;
methods;
Reproducibility of Results;
Sensitivity and Specificity
- From:
Journal of Biomedical Engineering
2011;28(4):814-829
- CountryChina
- Language:Chinese
-
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.
