0000000001134303
AUTHOR
Philip Heraud
showing 3 related works from this author
Infrared based saliva screening test for COVID‐19
2021
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in an unprecedented need for diagnostic testing that is critical in controlling the spread of COVID-19. We propose a portable infrared spectrometer with purpose-built transflection accessory for rapid point-of-care detection of COVID-19 markers in saliva. Initially, purified virion particles were characterized with Raman spectroscopy, synchrotron infrared (IR) and AFM-IR. A data set comprising 171 transflection infrared spectra from 29 subjects testing positive for SARS-CoV-2 by RT-qPCR and 28 testing negative, was modeled using Monte Carlo Double Cross Validation with 50 randomized test and model sets. The testing se…
Comparison of transflection and transmission FTIR imaging measurements performed on differentially fixed tissue sections
2015
The widespread and cost-effective use of transflection substrates in Fourier transform infrared (FTIR) imaging of clinical samples is affected by the presence of artefacts including the electric field standing wave (EFSW) and contributions from light dispersion. For IR-based diagnostics, the manifestation of undesirable artifacts can distort the spectra and lead to erroneous diagnosis. Nevertheless, there is no clear consensus in the literature about the degree of influence of these effects. The aim of this work is to contribute to this discussion by comparing transflection and transmission images of the same tissue. For this purpose two adjacent sections of the same tissue (lymphoma sample…
Dataset and Data analysis for "Infrared based saliva screening test for COVID-19"
2021
External Modelling 1 is the Quasar .ows model to process the Source data 1 to generate the PCA plot shown in Figure 4B and loadings plots in Figure 4C. External Modelling 2 is the MCDCV-PLS-DA Matlab model that can be used in combination with PLS-Tool Box to generate the Receiver Operating Curves (ROC) and the prediction model shown in Figures 4D and 4E, respectively. Source Data 1 is for the PCA modelling. Source Data 2 for the MCDCV-PLS-DA.