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

Arni S.R. Srinivasa Rao; Jose A. Vazquez

doi:10.1017/ice.2020.61

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

Arni S.R. Srinivasa Rao, Jose A. Vazquez

Research output: Contribution to journal › Review article › peer-review

247 Scopus citations

Abstract

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.

Original language	English (US)
Pages (from-to)	826-830
Number of pages	5
Journal	Infection Control and Hospital Epidemiology
Volume	41
Issue number	7
DOIs	https://doi.org/10.1017/ice.2020.61
State	Published - Jul 1 2020

ASJC Scopus subject areas

Epidemiology
Microbiology (medical)
Infectious Diseases

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1017/ice.2020.61

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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.
In: Infection Control and Hospital Epidemiology, Vol. 41, No. 7, 01.07.2020, p. 826-830.

Research output: Contribution to journal › Review article › peer-review

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

Abstract

ASJC Scopus subject areas

UN SDGs

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