tetano
Editor, Senior Moderator
Sci Rep
. 2020 Nov 4;10(1):19012.
doi: 10.1038/s41598-020-75912-x.
An artificial intelligence-based first-line defence against COVID-19: digitally screening citizens for risks via a chatbot
Alistair Martin[SUP] 1 [/SUP], Jama Nateqi[SUP] 2 3 [/SUP], Stefanie Gruarin[SUP] 4 [/SUP], Nicolas Munsch[SUP] 1 [/SUP], Isselmou Abdarahmane[SUP] 1 [/SUP], Marc Zobel[SUP] 1 [/SUP], Bernhard Knapp[SUP] 1 [/SUP]
Affiliations
Abstract
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 .
. 2020 Nov 4;10(1):19012.
doi: 10.1038/s41598-020-75912-x.
An artificial intelligence-based first-line defence against COVID-19: digitally screening citizens for risks via a chatbot
Alistair Martin[SUP] 1 [/SUP], Jama Nateqi[SUP] 2 3 [/SUP], Stefanie Gruarin[SUP] 4 [/SUP], Nicolas Munsch[SUP] 1 [/SUP], Isselmou Abdarahmane[SUP] 1 [/SUP], Marc Zobel[SUP] 1 [/SUP], Bernhard Knapp[SUP] 1 [/SUP]
Affiliations
- PMID: 33149198
- DOI: 10.1038/s41598-020-75912-x
Abstract
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 .