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Study on the echinococcosis blood serum detection based on Raman spectroscopy combined with neural network 被引量:2
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作者 CHENG Jin-ying XU Liang +4 位作者 LU Guo-dong TANG Jun MO Jia-qing LU Xiao-yi GAO Zhi-xian 《Optoelectronics Letters》 EI 2017年第1期77-80,共4页
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... 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. 展开更多
关键词 echinococcosis normalized reflectivity BPNN distribute consuming iteration spectrometer atypical immunology
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