Author:
Munsch Nicolas,Martin Alistair,Gruarin Stefanie,Nateqi Jama,Abdarahmane Isselmou,Weingartner-Ortner Rafael,Knapp Bernhard
Abstract
AbstractBackgroundA large number of online COVID-19 symptom checkers and chatbots have been developed but anecdotal evidence suggests that their conclusions are highly variable. To our knowledge, no study has evaluated the accuracy of COVID-19 symptom checkers in a statistically rigorous manner.MethodsIn this paper, we evaluate 10 different COVID-19 symptom checkers screening 50 COVID-19 case reports alongside 410 non-COVID-19 control cases.ResultsWe find that the number of correctly assessed cases varies considerably between different symptom checkers, with Symptoma (F1=0.92, MCC=0.85) showing the overall best performance followed by Infermedica (F1=0.80, MCC=0.61).
Publisher
Cold Spring Harbor Laboratory
Reference12 articles.
1. Tasnim S , Hossain M , Mazumder H . Impact of rumors or misinformation on coronavirus disease (COVID-19) in social media.: 8.
2. Evaluation of symptom checkers for self diagnosis and triage: audit study
3. Chambers D , Cantrell A , Johnson M , Preston L , Baxter SK , Booth A , et al. Digital and online symptom checkers and assessment services for urgent care to inform a new digital platform: a systematic review. Southampton (UK): NIHRJournals Library; 2019. Available: http://www.ncbi.nlm.nih.gov/books/NBK545124/
4. I asked eight chatbots whether I had Covid-19. The answers ranged from ‘low’ risk to ‘start home isolation.’ Available: https://www.statnews.com/2020/03/23/coronavirus-i-asked-eight-chatbots-whether-i-had-covid-19/
5. Report of the WHO-china joint mission on coronavirus disease 2019 (covid-19). 2020. Available: https://www.who.int/docs/default-source/coronaviruse/who-china-joint-mission-on-covid-19-final-report.pdf
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