{"doi":"10.1371/journal.pone.0252121","title":"Proof of concept for real-time detection of SARS CoV-2 infection with an electronic nose","abstract":"<jats:p>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.</jats:p>","journal":"PLOS ONE","year":2021,"id":626541,"datarank":0.5983476069846413,"base_score":3.9889840465642745,"endowment":3.9889840465642745,"self_citation_contribution":0.5983476069846413,"citation_network_contribution":0.0,"self_endowment_contribution":0.5983476069846413,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":53,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1620749,"name":"Michal Andelman-Gur","orcid":null,"position":1,"is_corresponding":false},{"id":1620750,"name":"Liron Pinchover","orcid":null,"position":2,"is_corresponding":false},{"id":1097705,"name":"Reut Weissgross","orcid":"0000-0002-6554-9462","position":3,"is_corresponding":false},{"id":1620752,"name":"Aharon Weissbrod","orcid":null,"position":4,"is_corresponding":false},{"id":1097706,"name":"Eva Mishor","orcid":"0000-0003-4006-3789","position":5,"is_corresponding":false},{"id":832770,"name":"Roni Zoller","orcid":null,"position":6,"is_corresponding":false},{"id":1620753,"name":"Vera Linetsky","orcid":null,"position":7,"is_corresponding":false},{"id":1620754,"name":"Abebe Medhanie","orcid":null,"position":8,"is_corresponding":false},{"id":1615679,"name":"Sagit Shushan","orcid":null,"position":9,"is_corresponding":false},{"id":1620755,"name":"Eli Jaffe","orcid":null,"position":10,"is_corresponding":false},{"id":1097708,"name":"Tali Weiss","orcid":"0000-0002-3232-9391","position":11,"is_corresponding":false},{"id":1620747,"name":"Kobi Snitz","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Proof of concept for real-time detection of SARS CoV-2 infection with an electronic nose","abstract":"<jats:p>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.</jats:p>","is_dataset_classified":null,"base_score":3.9889840465642745,"endowment":3.9889840465642745,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"34077435","pmcid":null,"openalex_id":"https://openalex.org/W3165466498","authors":[],"funders":[{"funder_name":"European Research Council AdG.","grant_id":"670798","title":"Social Chemosignaling as a Factor in Human Behavior in both Health and Disease"},{"funder_name":"Horizon 2020 FET Open project","grant_id":"662629","title":"NanoSmells: Artificial remote-controlled odorants"},{"funder_name":"European Research Council","grant_id":"","title":null}],"total_grants":3,"fwci":3.1224,"citation_percentile":0.92454855,"influential_citations":0,"citation_trend":[{"year":2022,"count":16},{"year":2023,"count":11},{"year":2024,"count":16},{"year":2025,"count":8},{"year":2026,"count":2}],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"https://doi.org/10.1371/journal.pone.0252121","host_type":"journal"},{"url":"https://doi.org/10.1371/journal.pone.0252121","host_type":"publisher"},{"url":"https://dx.plos.org/10.1371/journal.pone.0252121","host_type":"publisher"},{"url":"https://pubmed.ncbi.nlm.nih.gov/34077435","host_type":"repository"},{"url":"https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0252121","host_type":"repository"},{"url":"https://doaj.org/article/ee4a37ed1d09479e95664ca61196d1f7","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8172018","host_type":"repository"},{"url":"https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0252121&type=printable","host_type":""},{"url":"http://dx.doi.org/10.1371/journal.pone.0252121","host_type":""},{"url":"https://dx.doi.org/10.1371/journal.pone.0252121","host_type":""}],"fields_of_study":["Advanced Chemical Sensor Technologies","Olfactory and Sensory Function Studies","Biosensors and Analytical Detection","03 medical and health sciences","0302 clinical medicine","Adult","COVID-19","Deep Learning","Electronic Nose","Female","Humans","Israel","Male","Middle Aged","Pandemics","Proof of Concept Study","SARS-CoV-2","Volatile Organic Compounds"],"mesh_terms":["Proof of Concept Study","Deep Learning","COVID-19","SARS-CoV-2","Adult","Female","Humans","Israel","Male","Middle Aged","Volatile Organic Compounds","Pandemics","Electronic Nose"],"keywords":["Electronic nose","Coronavirus disease 2019 (COVID-19)","Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)","2019-20 coronavirus outbreak","Pandemic","Odor","Proof of concept","Computer science","Artificial intelligence","Software deployment","Virology","Medicine","Pathology","Biology","Infectious disease (medical specialty)","Neuroscience","Adult","Male","Volatile Organic Compounds","SARS-CoV-2","Science","Q","R","COVID-19","Middle Aged","Proof of Concept Study","Deep Learning","Humans","Female","Israel","Pandemics","Research Article"],"sdg_mappings":[{"sdg_number":3,"sdg_label":"3. Good health"},{"sdg_number":8,"sdg_label":"8. Economic growth"},{"sdg_number":0,"sdg_label":"Good health and well-being"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-04T14:17:11.173709Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}