Diagnostic prediction of early silicosis patients using neural network and MALDI-TOF-MS in serum / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 142-147, 2011.
Artigo
em Chinês
| WPRIM
| ID: wpr-306604
ABSTRACT
Serum of 79 workers exposed to silica and 25 healthy controls cases were determined by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). 7 protein peaks were selected and used by artificial neural network (ANN) to establish a diagnostic model. A blinded test showed that accuracy, sensitivity and specificity were 91.35%, 93.69%, and 84.52%, respectively. The diagnostic pattern was also established to distinguish each stage of silica-exposed population. The diagnostic pattern worked excellently with 89.23%, 94.20% and 92.37% of accurate rate for classifying phase 0, phase 0+, and phase I of silicosis, respectively.
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Assunto principal:
Silicose
/
Sangue
/
Proteínas Sanguíneas
/
Biomarcadores
/
Sensibilidade e Especificidade
/
Classificação
/
Redes Neurais de Computação
/
Espectrometria de Massas por Ionização e Dessorção a Laser Assistida por Matriz
/
Diagnóstico
/
Métodos
Tipo de estudo:
Estudo diagnóstico
/
Estudo prognóstico
Limite:
Humanos
Idioma:
Chinês
Revista:
Journal of Biomedical Engineering
Ano de publicação:
2011
Tipo de documento:
Artigo
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