Rapid diagnosis of latent and active pulmonary tuberculosis by autofluorescence spectroscopy of blood plasma combined with artificial neural network algorithm

•A rapid, accurate, label-free and non-invasive diagnosis method of pulmonary tuberculosis (TB) has been developed by using plasma autofluorescence spectroscopy and Machine Learning algorithm.•It is the first time that the autofluorescence spectroscopy combined with optimized three-classification Ar...

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Vydáno v:	Photodiagnosis and photodynamic therapy Ročník 50; s. 104426
Hlavní autoři:	Yue, Fengjiao, Li, Si, Wu, Lijuan, Chen, Xuerong, Zhu, Jianhua
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Netherlands Elsevier B.V 01.12.2024 Elsevier
Témata:	Adult Algorithms Artificial neural network Autofluorescence spectroscopy Blood plasma Female Humans Latent Tuberculosis - diagnosis Linear discriminant analysis Male Middle Aged Neural Networks, Computer Principal component analysis Pulmonary tuberculosis Spectrometry, Fluorescence - methods Tuberculosis, Pulmonary - blood Tuberculosis, Pulmonary - diagnosis Autofluorescence spectroscopy Artificial neural network Linear discriminant analysis Pulmonary tuberculosis Blood plasma Principal component analysis
ISSN:	1572-1000, 1873-1597, 1873-1597
On-line přístup:	Získat plný text
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