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Artificial Intelligence (AI) and data science-based policy response to COVID-19 in low and middle-income countries

Artificial Intelligence (AI) and data science-based policy response to COVID-19 in low and middle-income countries
Artificial Intelligence (AI) and data science-based policy response to COVID-19 in low and middle-income countries
Tahir M. Nisar and Henry Agyei-Boapeah discuss how effectively low and middle-income (LMICs) can tackle the challenge of COVID-19 by designing and implementing AI and data science-based policy responses.
Nisar, Tahir M.
6b1513b5-23d1-4151-8dd2-9f6eaa6ea3a6
Agyei-Boapeah, Henry
37005f29-d453-458e-b6b5-cd92e55587a4
Nisar, Tahir M.
6b1513b5-23d1-4151-8dd2-9f6eaa6ea3a6
Agyei-Boapeah, Henry
37005f29-d453-458e-b6b5-cd92e55587a4

Nisar, Tahir M. and Agyei-Boapeah, Henry (2021) Artificial Intelligence (AI) and data science-based policy response to COVID-19 in low and middle-income countries. Global Policy Journal.

Record type: Article

Abstract

Tahir M. Nisar and Henry Agyei-Boapeah discuss how effectively low and middle-income (LMICs) can tackle the challenge of COVID-19 by designing and implementing AI and data science-based policy responses.

Text
Paper AI and Data Science in LMICs Revised (2) - Accepted Manuscript
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More information

Accepted/In Press date: 7 January 2021
Published date: 7 January 2021

Identifiers

Local EPrints ID: 447337
URI: http://eprints.soton.ac.uk/id/eprint/447337
PURE UUID: ae333cb6-f5e6-40fb-a46a-e9fcbb6367f4
ORCID for Tahir M. Nisar: ORCID iD orcid.org/0000-0003-2240-5327
ORCID for Henry Agyei-Boapeah: ORCID iD orcid.org/0000-0003-4798-6324

Catalogue record

Date deposited: 09 Mar 2021 17:33
Last modified: 10 Mar 2021 02:58

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Contributors

Author: Tahir M. Nisar ORCID iD
Author: Henry Agyei-Boapeah ORCID iD

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