NDLI: Study on the echinococcosis blood serum detection based on Raman spectroscopy combined with neural network

Content Provider	Springer Nature Link
Author	Cheng, Jin ying Xu, Liang Lü, Guo dong Tang, Jun Mo, Jia qing Lü, Xiao yi Gao, Zhi xian
Copyright Year	2017
Abstract	A Raman spectroscopy method combined with neural network is used for the invasive and rapid detection of echinococcosis. The Raman spectroscopy measurements are performed on two groups of blood serum samples, which are from 28 echinococcosis patients and 38 healthy persons, respectively. The normalized Raman reflection spectra show that the reflectivity of the echinococcosis blood serum is higher than that of the normal human blood serum in the wavelength ranges of 101—175 nm and 1 801—2 701 nm. Then the principal component analysis (PCA) and back propagation neural network (BPNN) model are used to obtain the diagnosis results. The diagnosis rates for healthy persons and echinococcosis persons are 93.333 3% and 90.909 1%, respectively, so the average final diagnosis rate is 92.121 2%. The results demonstrate that the Raman spectroscopy analysis of blood serum combined with PCA-BPNN has considerable potential for the non-invasive and rapid detection of echinococcosis.
Starting Page	77
Ending Page	80
Page Count	4
File Format	PDF
ISSN	16731905
Journal	Optoelectronics Letters
Volume Number	13
Issue Number	1
e-ISSN	19935013
Language	English
Publisher	Tianjin University of Technology
Publisher Date	2017-01-11
Publisher Place	Tianjin
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Optics, Lasers, Photonics, Optical Devices
Content Type	Text
Resource Type	Article
Subject	Atomic and Molecular Physics, and Optics Condensed Matter Physics Electronic, Optical and Magnetic Materials Electrical and Electronic Engineering

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