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The study on the early diagnosis of hypoxic ischemic encephalopathy (HIE) in the newborns by fuzzy BP neural networks / 生物医学工程学杂志
Article em Zh | WPRIM | ID: wpr-359174
Biblioteca responsável: WPRO
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.
Assuntos
Texto completo: 1 Índice: WPRIM Assunto principal: Algoritmos / Reconhecimento Automatizado de Padrão / Reprodutibilidade dos Testes / Diagnóstico por Computador / Sensibilidade e Especificidade / Redes Neurais de Computação / Lógica Fuzzy / Hipóxia-Isquemia Encefálica / Diagnóstico Precoce / Diagnóstico Tipo de estudo: Diagnostic_studies / Prognostic_studies / Screening_studies Limite: Female / Humans / Male / Newborn Idioma: Zh Revista: Journal of Biomedical Engineering Ano de publicação: 2011 Tipo de documento: Article
Texto completo: 1 Índice: WPRIM Assunto principal: Algoritmos / Reconhecimento Automatizado de Padrão / Reprodutibilidade dos Testes / Diagnóstico por Computador / Sensibilidade e Especificidade / Redes Neurais de Computação / Lógica Fuzzy / Hipóxia-Isquemia Encefálica / Diagnóstico Precoce / Diagnóstico Tipo de estudo: Diagnostic_studies / Prognostic_studies / Screening_studies Limite: Female / Humans / Male / Newborn Idioma: Zh Revista: Journal of Biomedical Engineering Ano de publicação: 2011 Tipo de documento: Article