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An artificial intelligence-based first-line defence against COVID-19: digitally screening citizens for risks via a chatbot
To combat the pandemic of the coronavirus disease 2019 (COVID-19), numerous governments have established phone hotlines to prescreen potential cases. These hotlines have struggled with the volume of callers, leading to wait times of hours or, even, an inability to contact health authorities. Symptom...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7643065/ https://www.ncbi.nlm.nih.gov/pubmed/33149198 http://dx.doi.org/10.1038/s41598-020-75912-x |
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author | Martin, Alistair Nateqi, Jama Gruarin, Stefanie Munsch, Nicolas Abdarahmane, Isselmou Zobel, Marc Knapp, Bernhard |
author_facet | Martin, Alistair Nateqi, Jama Gruarin, Stefanie Munsch, Nicolas Abdarahmane, Isselmou Zobel, Marc Knapp, Bernhard |
author_sort | Martin, Alistair |
collection | PubMed |
description | To combat the pandemic of the coronavirus disease 2019 (COVID-19), numerous governments have established phone hotlines to prescreen potential cases. These hotlines have struggled with the volume of callers, leading to wait times of hours or, even, an inability to contact health authorities. Symptoma is a symptom-to-disease digital health assistant that can differentiate more than 20,000 diseases with an accuracy of more than 90%. We tested the accuracy of Symptoma to identify COVID-19 using a set of diverse clinical cases combined with case reports of COVID-19. We showed that Symptoma can accurately distinguish COVID-19 in 96.32% of clinical cases. When considering only COVID-19 symptoms and risk factors, Symptoma identified 100% of those infected when presented with only three signs. Lastly, we showed that Symptoma’s accuracy far exceeds that of simple “yes–no” questionnaires widely available online. In summary, Symptoma provides unparalleled accuracy in systematically identifying cases of COVID-19 while also considering over 20,000 other diseases. Furthermore, Symptoma allows free text input, furthered with disease-specific follow up questions, in 36 languages. Combined, these results and accessibility give Symptoma the potential to be a key tool in the global fight against COVID-19. The Symptoma predictor is freely available online at https://www.symptoma.com. |
format | Online Article Text |
id | pubmed-7643065 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-76430652020-11-06 An artificial intelligence-based first-line defence against COVID-19: digitally screening citizens for risks via a chatbot Martin, Alistair Nateqi, Jama Gruarin, Stefanie Munsch, Nicolas Abdarahmane, Isselmou Zobel, Marc Knapp, Bernhard Sci Rep Article To combat the pandemic of the coronavirus disease 2019 (COVID-19), numerous governments have established phone hotlines to prescreen potential cases. These hotlines have struggled with the volume of callers, leading to wait times of hours or, even, an inability to contact health authorities. Symptoma is a symptom-to-disease digital health assistant that can differentiate more than 20,000 diseases with an accuracy of more than 90%. We tested the accuracy of Symptoma to identify COVID-19 using a set of diverse clinical cases combined with case reports of COVID-19. We showed that Symptoma can accurately distinguish COVID-19 in 96.32% of clinical cases. When considering only COVID-19 symptoms and risk factors, Symptoma identified 100% of those infected when presented with only three signs. Lastly, we showed that Symptoma’s accuracy far exceeds that of simple “yes–no” questionnaires widely available online. In summary, Symptoma provides unparalleled accuracy in systematically identifying cases of COVID-19 while also considering over 20,000 other diseases. Furthermore, Symptoma allows free text input, furthered with disease-specific follow up questions, in 36 languages. Combined, these results and accessibility give Symptoma the potential to be a key tool in the global fight against COVID-19. The Symptoma predictor is freely available online at https://www.symptoma.com. Nature Publishing Group UK 2020-11-04 /pmc/articles/PMC7643065/ /pubmed/33149198 http://dx.doi.org/10.1038/s41598-020-75912-x Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Martin, Alistair Nateqi, Jama Gruarin, Stefanie Munsch, Nicolas Abdarahmane, Isselmou Zobel, Marc Knapp, Bernhard An artificial intelligence-based first-line defence against COVID-19: digitally screening citizens for risks via a chatbot |
title | An artificial intelligence-based first-line defence against COVID-19: digitally screening citizens for risks via a chatbot |
title_full | An artificial intelligence-based first-line defence against COVID-19: digitally screening citizens for risks via a chatbot |
title_fullStr | An artificial intelligence-based first-line defence against COVID-19: digitally screening citizens for risks via a chatbot |
title_full_unstemmed | An artificial intelligence-based first-line defence against COVID-19: digitally screening citizens for risks via a chatbot |
title_short | An artificial intelligence-based first-line defence against COVID-19: digitally screening citizens for risks via a chatbot |
title_sort | artificial intelligence-based first-line defence against covid-19: digitally screening citizens for risks via a chatbot |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7643065/ https://www.ncbi.nlm.nih.gov/pubmed/33149198 http://dx.doi.org/10.1038/s41598-020-75912-x |
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