Identification of COVID-19 Can be Quicker through Artificial Intelligence framework using a Mobile Phone-Based Survey in the Populations when Cities/Towns Are Under Quarantine.
Identifieur interne : 000331 ( an2020/Analysis ); précédent : 000330; suivant : 000332Identification of COVID-19 Can be Quicker through Artificial Intelligence framework using a Mobile Phone-Based Survey in the Populations when Cities/Towns Are Under Quarantine.
Auteurs : Arni S R Srinivasa Rao ; Jose A. VazquezSource :
- Infection control and hospital epidemiology [ 1559-6834 ] ; 2020.
Abstract
We are proposing to use machine learning algorithms to be able to improve possible case identifications of COVID-19 more quicker when we use a mobile phone-based web survey. This will also reduce the spread in the susceptible populations.
DOI: 10.1017/ice.2020.61
PubMed: 32122430
Affiliations:
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Vazquez</name><affiliation><nlm:affiliation>Chief and Professor, Division of Infectious Diseases, Department of Medicine, Medical College of Georgia, Augusta University, 1120, 15th Street, AE 1015 Augusta, GA, 30912, USA Tel: +1-706-723-0105 (office).</nlm:affiliation><wicri:noCountry code="subField">USA Tel: +1-706-723-0105 (office)</wicri:noCountry></affiliation></author></analytic><series><title level="j">Infection control and hospital epidemiology</title><idno type="eISSN">1559-6834</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">We are proposing to use machine learning algorithms to be able to improve possible case identifications of COVID-19 more quicker when we use a mobile phone-based web survey. 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