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Application of Raman spectroscopy in the detection of hepatitis B virus infection

Autor: Dongni Tong, Xiangxiang Zheng, Xiaoyi Lv, Guodong Lv, JingJing Zhang, Zhaoxia Zhang, Cheng Chen

Publikováno v: Photodiagnosis and Photodynamic Therapy. 28:248-252

Objective Detection of hepatitis B virus (HBV) using Raman spectroscopy. Methods Raman spectroscopy was used to examine the serum samples of 500 patients with HBV and 500 non-HBV persons. First, the adaptive iterative weighted penalty least squares m

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4dbeb1a689d118650492df944c438803
https://doi.org/10.1016/j.pdpdt.2019.08.006

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Exploration research on the fusion of multimodal spectrum technology to improve performance of rapid diagnosis scheme for thyroid dysfunction

Autor: Guodong Lv, Hongyi Li, Jun Tang, Guoli Du, Dongni Tong, Rumeng Si, Jiaqing Mo, Xiaoyi Lv, Hongbing Ma, Cheng Chen

Publikováno v: Journal of biophotonicsREFERENCES. 13(2)

The spectral fusion by Raman spectroscopy and Fourier infrared spectroscopy combined with pattern recognition algorithms is utilized to diagnose thyroid dysfunction serum, and finds the spectral segment with the highest sensitivity to further advance

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fa9969686bc6d3b0e7a6baea7ebb6117
https://pubmed.ncbi.nlm.nih.gov/31593625

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Serum Raman spectroscopy combined with a multi-feature fusion convolutional neural network diagnosing thyroid dysfunction

Autor: Dongni Tong, Xiaoyi Lv, Hongmei Li, Zhiqi Guo, Hao Chen, Rumeng Si, Chen Chen, Hongyi Li, Cheng Chen, Huicheng Lai, Hang Wang

Publikováno v: Optik. 216:164961

In this study, serum samples from 199 patients with thyroid dysfunction and 183 people with normal thyroid function were collected by Raman spectroscopy, and the data were dimensions-reduced by PCA. The reduced data were input into a multi-feature fu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::511057c563f7d9d98cde0872f64072a4
https://doi.org/10.1016/j.ijleo.2020.164961

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