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.
Article
in Chinese
| 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.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Silicosis
/
Blood
/
Blood Proteins
/
Biomarkers
/
Sensitivity and Specificity
/
Classification
/
Neural Networks, Computer
/
Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
/
Diagnosis
/
Methods
Type of study:
Diagnostic study
/
Prognostic study
Limits:
Humans
Language:
Chinese
Journal:
Journal of Biomedical Engineering
Year:
2011
Type:
Article
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