Journal
JOURNAL OF BIOPHOTONICS
Volume 13, Issue 10, Pages -Publisher
WILEY-V C H VERLAG GMBH
DOI: 10.1002/jbio.202000189
Keywords
GUI-based automated computational analysis; linear discriminant analysis; principal component analysis; Raman spectroscopy; RNA virus
Categories
Ask authors/readers for more resources
Several non-invasive Raman spectroscopy-based assays have been reported for rapid and sensitive detection of pathogens. We developed a novel statistical model for the detection of RNA viruses in saliva, based on an unbiased selection of a set of 65 Raman spectral features that mostly attribute to the RNA moieties, with a prediction accuracy of 91.6% (92.5% sensitivity and 88.8% specificity). Furthermore, to minimize variability and automate the downstream analysis of the Raman spectra, we developed a GUI-based analytical tool RNA Virus Detector (RVD). This conceptual framework to detect RNA viruses in saliva could form the basis for field application of Raman Spectroscopy in managing viral outbreaks, such as the ongoing COVID-19 pandemic. ().
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available