Identification of COVID-19 can be quicker through artificial intelligence framework using a mobile phone–based survey when cities and towns are under quarantine

We propose the use of a machine learning algorithm to improve possible COVID-19 case identification more quickly using a mobile phone–based web survey. This method could reduce the spread of the virus in susceptible populations under quarantine.

Detalles Bibliográficos
Autores principales: Srinivasa Rao, Arni S. R., Vazquez, Jose A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2020
Materias:
Commentary
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7200852/
https://www.ncbi.nlm.nih.gov/pubmed/32122430
http://dx.doi.org/10.1017/ice.2020.61
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author Srinivasa Rao, Arni S. R.
Vazquez, Jose A.
author_facet Srinivasa Rao, Arni S. R.
Vazquez, Jose A.
author_sort Srinivasa Rao, Arni S. R.
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description We propose the use of a machine learning algorithm to improve possible COVID-19 case identification more quickly using a mobile phone–based web survey. This method could reduce the spread of the virus in susceptible populations under quarantine.
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spelling pubmed-72008522020-05-06 Identification of COVID-19 can be quicker through artificial intelligence framework using a mobile phone–based survey when cities and towns are under quarantine Srinivasa Rao, Arni S. R. Vazquez, Jose A. Infect Control Hosp Epidemiol Commentary We propose the use of a machine learning algorithm to improve possible COVID-19 case identification more quickly using a mobile phone–based web survey. This method could reduce the spread of the virus in susceptible populations under quarantine. Cambridge University Press 2020-03-04 /pmc/articles/PMC7200852/ /pubmed/32122430 http://dx.doi.org/10.1017/ice.2020.61 Text en © The Society for Healthcare Epidemiology of America 2020 http://creativecommons.org/licenses/by/4.0/ This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Commentary
Srinivasa Rao, Arni S. R.
Vazquez, Jose A.
Identification of COVID-19 can be quicker through artificial intelligence framework using a mobile phone–based survey when cities and towns are under quarantine
title Identification of COVID-19 can be quicker through artificial intelligence framework using a mobile phone–based survey when cities and towns are under quarantine
title_full Identification of COVID-19 can be quicker through artificial intelligence framework using a mobile phone–based survey when cities and towns are under quarantine
title_fullStr Identification of COVID-19 can be quicker through artificial intelligence framework using a mobile phone–based survey when cities and towns are under quarantine
title_full_unstemmed Identification of COVID-19 can be quicker through artificial intelligence framework using a mobile phone–based survey when cities and towns are under quarantine
title_short Identification of COVID-19 can be quicker through artificial intelligence framework using a mobile phone–based survey when cities and towns are under quarantine
title_sort identification of covid-19 can be quicker through artificial intelligence framework using a mobile phone–based survey when cities and towns are under quarantine
topic Commentary
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7200852/
https://www.ncbi.nlm.nih.gov/pubmed/32122430
http://dx.doi.org/10.1017/ice.2020.61
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