Analysis of Research Projects Focusing on Artificial Intelligence and Digital Technologies to Fight COVID-19

Authors

DOI:

https://doi.org/10.9771/cp.v16i2.50578

Keywords:

Covid-19, Research and Innovation, Technology.

Abstract

In 2020, the World Health Organization declared that the COVID-19 pandemic become a public health emergency of international concern. Thus, investments from various countries and continents have emerged in research projects and technological innovation aimed at mitigating this global problem. This article aims to evaluate the Science, Technology and Innovation (ST&I) projects concerning solutions using Artificial Intelligence (IA) and related technology to fight COVID-19 that received funding in the period from 2020 to 2022 and were registered on the Orbit Insight platform. Regarding the institutions responsible for the projects, 50% are companies, 23% are institutes, 20% are universities, and 7% are from the United States government. Regarding the countries that have invested the most, 57.14% are funded by the European Commission and 42.86% are funded by the United States.

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Author Biographies

Karla Susiane dos Santos Pereira, Federal University of Amazonas, Manaus, AM, Brazil

Master in Informatics from the Federal University of Amazonas in 2017; scholarship holder by FAPEAM.

Daniel Reis Armond de Melo, Federal University of Amazonas, Manaus, AM, Brazil

PhD in Business Administration from the Federal University of Bahia, in 2012; scholarship holder by FAPEAM.

Dalton Chaves Vilela Junior, Federal University of Amazonas, Manaus, AM, Brazil

PhD in Business Administration from the Federal University of Rio Grande do Sul in 2010.

Lana Goncalves Rodrigues, Federal University of Amazonas, Manaus, AM, Brazil

Graduated in Business Administration from the Federal University of Amazonas in 2019; scholarship holder by FAPEAM.

References

ABD-ALRAZAQ, A. et al. Overview of technologies implemented during the first wave of the covid-19 pandemic: scoping review. Journal of Medical Internet Research, Pittsburgh, v. 23, n. 9, p. 1-18, set. 2021. Disponível em: https://www.jmir.org/2021/9/e29136. Acesso em: 19 jun. 2022.

ADADI, A.; LAHMER, M.; NASIRI, S. Artificial intelligence and covid-19: A systematic umbrella review and roads ahead. Journal of King Saud University – Computer and Information Sciences, [s.l.], Elsevier BV, p. 1-23, jul. 2021. Disponível em: https://www.sciencedirect.com/science/article/pii/S1319157821001774?via%3Dihub. Acesso em: 19 jun. 2022.

AMORIM, J. Q.; SALES, G. A. W.; GRECCO, M. C. P. Covid-19 e os impactos nas políticas de financiamento e investimento. Revista de Administração Mackenzie, São Paulo, v. 23, n. 2, p. 1-27, fev. 2022. Disponível em: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-69712022000200401&lng=en&nrm=iso. Acesso em: 19 jun. 2022.

ARJONA, R.; SAMSON, R. The role of research and innovation in support of europe’s recovery from the covid-19 crisis. R&I Paper Series Policy Brief, Luxembourg, p. 1-9, maio 2020. Disponível em: https://ec.europa.eu/info/sites/default/files/research_and_innovation/strategy_o. Acesso em: 21 jun. 2022.

BULLOCK, J. et al. Mapping the landscape of artificial intelligence applications against COVID-19. Journal of Artificial Intelligence Research, El Segundo, v. 69, p. 807-845, maio, 2020. Disponível em: https://www.jair.org/index.php/jair/article/view/12162. Acesso em: 21 jun. 2022.

CHANG, Z. et al. Application of artificial intelligence in covid-19 medical area: a systematic review. Journal of Thoracic Disease, [s.l.], v. 13, n. 12, p. 7.034-7.053, 2021. Disponível em: https://jtd.amegroups.com/article/view/56141/html. Acesso em: 21 jun. 2022.

DE NEGRI, F.; KOELLER, P. Políticas públicas para pesquisa e inovação em face da crise da covid-19. 2020. Disponível em: https://www.ipea.gov.br/portal/images/stories/PDFs/nota_tecnica/200520_nota_tecnica_diset_n_64.pdf. Acesso em: 20 jun. 2022.

DE NEGRI, F. et al. Ciência e tecnologia frente à pandemia: como a pesquisa científica e a inovação estão ajudando a combater o novo coronavírus no Brasil e no mundo. 2020. Disponível em: https:// www.ipea.gov.br/cts/pt/central-15 de-conteudo/artigos/artigos/182-corona. Acesso em: 05 ago. 2022.

FRY, C. et al. Consolidation in a crisis: Patterns of international collaboration in early Covid-19 research. Plos One, Estados Unidos, v. 15, n. 7, p. 1-15, jul. 2020. Disponível em: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0236307. Acesso em: 20 jun. 2022.

GOLINELLI, D. et al. Adoption of digital technologies in health care during the covid-19 pandemic: systematic review of early scientific literature. Journal of Medical Internet Research, [s.l.], v. 22, n. 11, p. 1-23, set. 2020. Disponível em: https://pubmed.ncbi.nlm.nih.gov/33079693/. Acesso em: 20 jun. 2022.

IPEA – INSTITUTO DE PESQUISA ECONÔMICA APLICADA. Países investem em pesquisa e inovação para superar a pandemia de covid-19. 2020. Disponível em: https://www.ipea.gov.br/portal/index.php?option=com_content&view=article&id=35588. Acesso em: 20 jun. 2022.

LALMUANAWMA, S.; HUSSAIN, J.; CHHAKCHHUAK, L. Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: A review. Chaos, Solitons & Fractals, [s.l.], v. 139, p. 1-6, jun. 2020. Disponível em: https://www.sciencedirect.com/science/article/pii/S0960077920304562?via%3Dihub. Acesso em: 20 jun. 2022.

LAVIN, A. et al. Technology readiness levels for machine learning systems. Nature Communications, London, n. 13, v. 6.039, p. 1-19, set. 2022. Disponível em: https://www.nature.com/articles/s41467-022-33128-9. Acesso em: 20 jun. 2022.

MATHIEU, E. et al. Coronavirus Pandemic (COVID-19). 2023. Disponível em: https://ourworldindata.org/coronavirus. Acesso em: 25 jan. 2023.

OLIVEIRA, E. A. et al. Covid-19 pandemic and the answer of science: a year in review. Anais da Academia Brasileira de Ciências, Rio de Janeiro, v. 93, n. 4, 2021. Disponível em: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652021000700702&lng=en&nrm=iso. Acesso em: 30 jun. 2022.

ROBERTS, M. et al. Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans. Nature Machine Intelligence, Londres, v. 3, p. 199-217, mar. 2021. Disponível em: https://www.nature.com/articles/s42256-021-00307-0. Acesso em: 28 jan. 2023.

Published

2023-03-15

How to Cite

Pereira, K. S. dos S., Melo, D. R. A. de ., Vilela Junior, D. C., & Rodrigues, L. G. (2023). Analysis of Research Projects Focusing on Artificial Intelligence and Digital Technologies to Fight COVID-19. Cadernos De Prospecção, 16(2), 455–471. https://doi.org/10.9771/cp.v16i2.50578

Issue

Section

Coronavirus (SARS-COV-2) e COVID-19