Selected article for: "discriminant analysis and statistical analysis"

Author: Zhang, Liyang; Xiao, Meng; Wang, Yao; Peng, Siqi; Chen, Yu; Zhang, Dong; Zhang, Dongheyu; Guo, Yuntao; Wang, Xinxin; Luo, Haiyun; Zhou, Qun; Xu, Yingchun
Title: Fast Screening and Primary Diagnosis of COVID-19 by ATR–FT-IR
  • Cord-id: b9e0dcfo
  • Document date: 2021_1_11
  • ID: b9e0dcfo
    Snippet: [Image: see text] The outbreak of coronavirus disease 2019 (COVID-19) has led to substantial infections and mortality around the world. Fast screening and diagnosis are thus crucial for quick isolation and clinical intervention. In this work, we showed that attenuated total reflection–Fourier transform infrared spectroscopy (ATR–FT-IR) can be a primary diagnostic tool for COVID-19 as a supplement to in-use techniques. It requires only a small volume (∼3 μL) of the serum sample and a short
    Document: [Image: see text] The outbreak of coronavirus disease 2019 (COVID-19) has led to substantial infections and mortality around the world. Fast screening and diagnosis are thus crucial for quick isolation and clinical intervention. In this work, we showed that attenuated total reflection–Fourier transform infrared spectroscopy (ATR–FT-IR) can be a primary diagnostic tool for COVID-19 as a supplement to in-use techniques. It requires only a small volume (∼3 μL) of the serum sample and a shorter detection time (several minutes). The distinct spectral differences and the separability between normal control and COVID-19 were investigated using multivariate and statistical analysis. Results showed that ATR–FT-IR coupled with partial least squares discriminant analysis was effective to differentiate COVID-19 from normal controls and some common respiratory viral infections or inflammation, with the area under the receiver operating characteristic curve (AUROC) of 0.9561 (95% CI: 0.9071–0.9774). Several serum constituents including, but not just, antibodies and serum phospholipids could be reflected on the infrared spectra, serving as “chemical fingerprints” and accounting for good model performances.

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