Zur Quantentheorie der Streuung und Dispersion

Smekal, Adolf

doi:10.1007/bf01494086

Cited by 14 publications

(6 citation statements)

References 9 publications

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“…12 This phenomenon was predicted in 1923 by Adolf Smekal and observed experimentally in 1928 by C.V. Raman and K.S. Krishnan 13,14 but the potential biomedical application of Raman spectroscopy did not emerge until 1970. 15 Raman scattering occurs when there is an exchange of energy between a sample and a monochromatic laser source emitting either visible or nearinfrared light.…”

Section: Raman Spectroscopymentioning

confidence: 95%

Saliva-based detection of COVID-19 infection in a real-world setting using reagent-free Raman spectroscopy and machine learning

Ember

Daoust

Mahfoud

et al. 2021

Preprint

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Significance: The primary method of COVID-19 detection is reverse transcription polymerase chain reaction (RT-PCR) testing. PCR test sensitivity may decrease as more variants of concern arise. Aim: We aimed to develop a reagent-free way to detect COVID-19 in a real-world setting with minimal constraints on sample acquisition. Approach: We present a workflow for collecting, preparing and imaging dried saliva supernatant droplets using a non-invasive, label-free technique known as Raman spectroscopy to detect changes in the molecular profile of saliva associated with COVID-19 infection. Results: Using machine learning and droplet segmentation, amongst all confounding factors, we discriminated between COVID-positive and negative individuals yielding receiver operating coefficient (ROC) curves with an area under curve (AUC) of 0.8 in both males (79% sensitivity, 75% specificity) and females (84% sensitivity, 64% specificity). Taking the sex of the saliva donor into account increased the AUC by 5%. Conclusion:These findings may pave the way for new rapid Raman spectroscopic screening tools for COVID-19 and other infectious diseases.

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Section: Raman Spectroscopymentioning

confidence: 95%

Saliva-based detection of COVID-19 infection in a real-world setting using reagent-free Raman spectroscopy and machine learning

Ember

Daoust

Mahfoud

et al. 2021

Preprint

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show abstract

“…It is a light-based technique, which measures the inelastic light scattered by matter, also called Raman scattering. 17 This phenomenon was predicted in 1928 by Smekal 18 and observed experimentally in 1928 by Raman and Krishnan, 19 but the potential biomedical application of Raman spectroscopy did not emerge until 1970. 20 Raman scattering occurs when there is an exchange of energy between a sample and a monochromatic laser source emitting either visible or near-infrared light.…”

Section: Introductionmentioning

confidence: 93%

Saliva-based detection of COVID-19 infection in a real-world setting using reagent-free Raman spectroscopy and machine learning

et al. 2022

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. Significance: The primary method of COVID-19 detection is reverse transcription polymerase chain reaction (RT-PCR) testing. PCR test sensitivity may decrease as more variants of concern arise and reagents may become less specific to the virus. Aim: We aimed to develop a reagent-free way to detect COVID-19 in a real-world setting with minimal constraints on sample acquisition. The machine learning (ML) models involved could be frequently updated to include spectral information about variants without needing to develop new reagents. Approach: We present a workflow for collecting, preparing, and imaging dried saliva supernatant droplets using a non-invasive, label-free technique—Raman spectroscopy—to detect changes in the molecular profile of saliva associated with COVID-19 infection. Results: We used an innovative multiple instance learning-based ML approach and droplet segmentation to analyze droplets. Amongst all confounding factors, we discriminated between COVID-positive and COVID-negative individuals yielding receiver operating coefficient curves with an area under curve (AUC) of 0.8 in both males (79% sensitivity and 75% specificity) and females (84% sensitivity and 64% specificity). Taking the sex of the saliva donor into account increased the AUC by 5%. Conclusion: These findings may pave the way for new rapid Raman spectroscopic screening tools for COVID-19 and other infectious diseases.

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“…The theoretical prediction of Raman scattering was made in 1923 by Smekal 7 and experimentally proven in 1928 by researchers from two independent groups: Raman and Krishnan 8 in India and Landsberg and Mandelstam 9 in Russia. However, the discovery of this phenomenon was attributed only to the first group, and the effect was not only named as a tribute to Raman but he also was awarded a Nobel Prize in Physics in the year 1930 in recognition of this achievement.…”

Section: History: From the Discovery Of The Pheno Menon To Spectroscomentioning

confidence: 99%

Raman Imaging Spectroscopy: History, Fundamentals and Current Scenario of the Technique

Mitsutake

Breitkreitz

2019

J. Braz. Chem. Soc.

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Raman imaging spectroscopy is a relatively new technique that has raised interest in several areas of knowledge due to the possibility of evaluating the spatial distribution of compounds based on their spectra. This paper presents a brief history of the development of this important technique, a theoretical description of the Raman effect and the preprocessing and processing (both univariate and multivariate) tools for Raman data. We also describe the current state of applications for major areas such as agriculture/biomass, environment, biology, medicine, pharmaceutical, geology, foodstuff, artwork, archaeology, material characterization and forensic.

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Zur Quantentheorie der Streuung und Dispersion

Cited by 14 publications

References 9 publications

Saliva-based detection of COVID-19 infection in a real-world setting using reagent-free Raman spectroscopy and machine learning

Saliva-based detection of COVID-19 infection in a real-world setting using reagent-free Raman spectroscopy and machine learning

Saliva-based detection of COVID-19 infection in a real-world setting using reagent-free Raman spectroscopy and machine learning

Raman Imaging Spectroscopy: History, Fundamentals and Current Scenario of the Technique

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