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Proof of concept for real-time detection of SARS CoV-2 infection with an electronic nose
Rapid diagnosis is key to curtailing the Covid-19 pandemic. One path to such rapid diagnosis may rely on identifying volatile organic compounds (VOCs) emitted by the infected body, or in other words, identifying the smell of the infection. Consistent with this rationale, dogs can use their nose to i...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8172018/ https://www.ncbi.nlm.nih.gov/pubmed/34077435 http://dx.doi.org/10.1371/journal.pone.0252121 |
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author | Snitz, Kobi Andelman-Gur, Michal Pinchover, Liron Weissgross, Reut Weissbrod, Aharon Mishor, Eva Zoller, Roni Linetsky, Vera Medhanie, Abebe Shushan, Sagit Jaffe, Eli Sobel, Noam |
author_facet | Snitz, Kobi Andelman-Gur, Michal Pinchover, Liron Weissgross, Reut Weissbrod, Aharon Mishor, Eva Zoller, Roni Linetsky, Vera Medhanie, Abebe Shushan, Sagit Jaffe, Eli Sobel, Noam |
author_sort | Snitz, Kobi |
collection | PubMed |
description | Rapid diagnosis is key to curtailing the Covid-19 pandemic. One path to such rapid diagnosis may rely on identifying volatile organic compounds (VOCs) emitted by the infected body, or in other words, identifying the smell of the infection. Consistent with this rationale, dogs can use their nose to identify Covid-19 patients. Given the scale of the pandemic, however, animal deployment is a challenging solution. In contrast, electronic noses (eNoses) are machines aimed at mimicking animal olfaction, and these can be deployed at scale. To test the hypothesis that SARS CoV-2 infection is associated with a body-odor detectable by an eNose, we placed a generic eNose in-line at a drive-through testing station. We applied a deep learning classifier to the eNose measurements, and achieved real-time detection of SARS CoV-2 infection at a level significantly better than chance, for both symptomatic and non-symptomatic participants. This proof of concept with a generic eNose implies that an optimized eNose may allow effective real-time diagnosis, which would provide for extensive relief in the Covid-19 pandemic. |
format | Online Article Text |
id | pubmed-8172018 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-81720182021-06-14 Proof of concept for real-time detection of SARS CoV-2 infection with an electronic nose Snitz, Kobi Andelman-Gur, Michal Pinchover, Liron Weissgross, Reut Weissbrod, Aharon Mishor, Eva Zoller, Roni Linetsky, Vera Medhanie, Abebe Shushan, Sagit Jaffe, Eli Sobel, Noam PLoS One Research Article Rapid diagnosis is key to curtailing the Covid-19 pandemic. One path to such rapid diagnosis may rely on identifying volatile organic compounds (VOCs) emitted by the infected body, or in other words, identifying the smell of the infection. Consistent with this rationale, dogs can use their nose to identify Covid-19 patients. Given the scale of the pandemic, however, animal deployment is a challenging solution. In contrast, electronic noses (eNoses) are machines aimed at mimicking animal olfaction, and these can be deployed at scale. To test the hypothesis that SARS CoV-2 infection is associated with a body-odor detectable by an eNose, we placed a generic eNose in-line at a drive-through testing station. We applied a deep learning classifier to the eNose measurements, and achieved real-time detection of SARS CoV-2 infection at a level significantly better than chance, for both symptomatic and non-symptomatic participants. This proof of concept with a generic eNose implies that an optimized eNose may allow effective real-time diagnosis, which would provide for extensive relief in the Covid-19 pandemic. Public Library of Science 2021-06-02 /pmc/articles/PMC8172018/ /pubmed/34077435 http://dx.doi.org/10.1371/journal.pone.0252121 Text en © 2021 Snitz et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Snitz, Kobi Andelman-Gur, Michal Pinchover, Liron Weissgross, Reut Weissbrod, Aharon Mishor, Eva Zoller, Roni Linetsky, Vera Medhanie, Abebe Shushan, Sagit Jaffe, Eli Sobel, Noam Proof of concept for real-time detection of SARS CoV-2 infection with an electronic nose |
title | Proof of concept for real-time detection of SARS CoV-2 infection with an electronic nose |
title_full | Proof of concept for real-time detection of SARS CoV-2 infection with an electronic nose |
title_fullStr | Proof of concept for real-time detection of SARS CoV-2 infection with an electronic nose |
title_full_unstemmed | Proof of concept for real-time detection of SARS CoV-2 infection with an electronic nose |
title_short | Proof of concept for real-time detection of SARS CoV-2 infection with an electronic nose |
title_sort | proof of concept for real-time detection of sars cov-2 infection with an electronic nose |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8172018/ https://www.ncbi.nlm.nih.gov/pubmed/34077435 http://dx.doi.org/10.1371/journal.pone.0252121 |
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