TY - JOUR
T1 - Proof of concept for real-time detection of SARS CoV-2 infection with an electronic nose
AU - Snitz, Kobi
AU - Andelman-Gur, Michal
AU - Pinchover, Liron
AU - Weissgross, Reut
AU - Weissbrod, Aharon
AU - Mishor, Eva
AU - Zoller, Roni
AU - Linetsky, Vera
AU - Medhanie, Abebe
AU - Shushan, Sagit
AU - Jaffe, Eli
AU - Sobel, Noam
N1 - Publisher Copyright:
© 2021 Snitz et al.
PY - 2021/6/1
Y1 - 2021/6/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85107036100&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0252121
DO - 10.1371/journal.pone.0252121
M3 - Article
C2 - 34077435
AN - SCOPUS:85107036100
SN - 1932-6203
VL - 16
JO - PLoS ONE
JF - PLoS ONE
IS - 6 June
M1 - e0252121
ER -