Three-step one-way model in terahertz biomedical detection

Abstract Terahertz technology has broad application prospects in biomedical detection. However, the mixed characteristics of actual samples make the terahertz spectrum complex and difficult to distinguish, and there is no practical terahertz detection method for clinical medicine. Here, we propose a...

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Main Authors: Peng, Yan (Author), Huang, Jieli (Author), Luo, Jie (Author), Yang, Zhangfan (Author), Wang, Liping (Author), Wu, Xu (Author), Zang, Xiaofei (Author), Yu, Chen (Author), Gu, Min (Author), Hu, Qing (Author), Zhang, Xicheng (Author), Zhu, Yiming (Author), Zhuang, Songlin (Author)
Format: Article
Language:English
Published: Springer Singapore, 2021-11-01T14:34:15Z.
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LEADER 01906 am a22002773u 4500
001 136927
042 |a dc 
100 1 0 |a Peng, Yan  |e author 
700 1 0 |a Huang, Jieli  |e author 
700 1 0 |a Luo, Jie  |e author 
700 1 0 |a Yang, Zhangfan  |e author 
700 1 0 |a Wang, Liping  |e author 
700 1 0 |a Wu, Xu  |e author 
700 1 0 |a Zang, Xiaofei  |e author 
700 1 0 |a Yu, Chen  |e author 
700 1 0 |a Gu, Min  |e author 
700 1 0 |a Hu, Qing  |e author 
700 1 0 |a Zhang, Xicheng  |e author 
700 1 0 |a Zhu, Yiming  |e author 
700 1 0 |a Zhuang, Songlin  |e author 
245 0 0 |a Three-step one-way model in terahertz biomedical detection 
260 |b Springer Singapore,   |c 2021-11-01T14:34:15Z. 
856 |z Get fulltext  |u https://hdl.handle.net/1721.1/136927 
520 |a Abstract Terahertz technology has broad application prospects in biomedical detection. However, the mixed characteristics of actual samples make the terahertz spectrum complex and difficult to distinguish, and there is no practical terahertz detection method for clinical medicine. Here, we propose a three-step one-way terahertz model, presenting a detailed flow analysis of terahertz technology in the biomedical detection of renal fibrosis as an example: 1) biomarker determination: screening disease biomarkers and establishing the terahertz spectrum and concentration gradient; 2) mixture interference removal: clearing the interfering signals in the mixture for the biomarker in the animal model and evaluating and retaining the effective characteristic peaks; and 3) individual difference removal: excluding individual interference differences and confirming the final effective terahertz parameters in the human sample. The root mean square error of our model is three orders of magnitude lower than that of the gold standard, with profound implications for the rapid, accurate and early detection of diseases. 
546 |a en 
655 7 |a Article