Artificial Intelligence in the Prevention of COVID-19: prospecting in the epidemiological context in the post-pandemic world
DOI:
https://doi.org/10.9771/cp.v16i2.50873Keywords:
Artificial Intelligence, Epidemiology, COVID-19.Abstract
The pandemic caused by COVID-19 motivated scientific and technological development to face it. Artificial Intelligence (AI) enters as a branch capable of assisting in epidemiological control and disease prevention. The objective of this article is to carry out scientific and technological prospecting on AI in the epidemiological and prevention context. Such information can contribute to combating new health crises. The Lens.org platform was used to investigate scientific works and patents relating AI, prevention, epidemiology and COVID-19. 57 articles and 19 patents were found, of these, one patent that cites an article and four patents that are cited in new technologies. It is observed that AI is an ally in epidemiological control, in the prevention and diagnosis of COVID-19 and can contribute to the analysis of large volumes of data, in the generation of control strategies, in the conduct of tests and in the creation of medicine or vaccines.
Downloads
References
BI, Qifang et al. Epidemiology and transmission of COVID-19 in 391 cases and 1286 of their close contacts in Shenzhen, China: a retrospective cohort study. The Lancet Infectious Diseases, [s.l.], v. 20, n. 8, p. 911-919, 2020. DOI: https://doi.org/10.1016/S1473-3099(20)30287-5.
CHEN, Jianguo et al. A survey on applications of artificial intelligence in fighting against COVID-19. ACM Computing Surveys (CSUR), [s.l.], v. 54, n. 8, p. 1-32, 2021. DOI: https://doi.org/10.1145/3465398.
COLLINS James J. et al. Massachusetts Inst Technology US, Massachusetts Gen Hospital US, Collins James J US, Bhattacharyya Roby. Depositante: WIPO, WO 2020/227530 A1, 2020.
DONG, Jiancheng et al. Application of big data and artificial intelligence in COVID-19 prevention, diagnosis, treatment and management decisions in China. Journal of Medical Systems, [s.l.], v. 45, n. 9, p. 1-11, 2021. DOI: https://doi.org/10.1007/s10916-021-01757-0.
FREITAS, Robson Almeida Borges et al. Prospecção científica sobre epidemiologia e prevenção da COVID-19 aliada a inteligência artificial. Cadernos de Prospecção, Salvador, v. 13, n. 2 COVID-19, p. 543-543, 2020. DOI: https://doi.org/10.9771/cp.v13i2.36190.
GAL, Ehrlich; MAIER, Fenster. Methods and systems of prioritizing treatments, vaccination, testing and/or activities while protecting the privacy of individuals, USA, US 11107588 B2, 2020.
GUIMARÃES, Reinaldo. Vacinas anticovid: um olhar da saúde coletiva. Ciência & Saúde Coletiva, [s.l.], v. 25, p. 3.579-3.585, 2020. DOI: https://doi.org/10.1590/1413-81232020259.24542020.
HOLMES, Elizabeth A. et al. Labrador Diagnostics LLC. Depositante: Integrated health data capture and analysis system, USA, US 11195624 B2. 2021.
HUANG, Shigao et al. Artificial intelligence in the diagnosis of COVID-19: Challenges and perspectives. International Journal of Biological Sciences, [s.l.], v. 17, n. 6, p. 1.581, 2021. DOI: https://doi.org/10.7150/ijbs.58855.
INFORME, E. N. S. P. et al. Fiocruz desenvolve novas vacinas para enfrentar Covid-19. [S.l.: s.n.], 2021.
JAMSHIDI, Mohammad et al. Artificial intelligence and COVID-19: deep learning approaches for diagnosis and treatment. Ieee Access, [s.l.], v. 8, p. 109581-109595, 2020. DOI: https://doi.org/10.1109/ACCESS.2020.3001973.
KHEMASUWAN, Danai; COLT, Henri G. Applications and challenges of AI-based algorithms in the COVID-19 pandemic. BMJ Innovations, [s.l.], v. 7, n. 2, 2021. DOI; http://dx.doi.org/10.1136/bmjinnov-2020-000648.
LENS.ORG. [Base de dados – Internet]. Cambia; Queensland University of Technology, 2020. Disponível em: https://www.lens.org/. Acesso em: 1º ago. 2022.
MAILLE, Baptiste et al. Smartwatch electrocardiogram and artificial intelligence for assessing cardiac-rhythm safety of drug therapy in the COVID-19 pandemic. The QT-logs study. International Journal of Cardiology, [s.l.], v. 331, p. 333-339, 2021. DOI: https://doi.org/10.1016/j.ijcard.2021.01.002.
MALIK, Yashpal Singh et al. How artificial intelligence may help the Covid‐19 pandemic: Pitfalls and lessons for the future. Reviews in Medical Virology, [s.l.], v. 31, n. 5, p. 1-11, 2021. DOI: https://doi.org/10.1002/rmv.2205.
NASEEM, Maleeha et al. Exploring the potential of artificial intelligence and machine learning to combat COVID-19 and existing opportunities for LMIC: a scoping review. Journal of Primary Care & Community Health, [s.l.], v. 11, p. 2150132720963634, 2020. DOI: https://doi.org/10.1177/2150132720963634.
OMS – ORGANIZAÇÃO MUNDIAL DE SAÚDE. Painel do Coronavírus da OMS (Covid). [2022]. Disponível em: https://covid19.who.int/. Acesso em: 27 ago. 2022.
PICCIALLI, Francesco et al. The role of artificial intelligence in fighting the COVID-19 pandemic. Information Systems Frontiers, [s.l.], v. 23, n. 6, p. 1.467-1.497, 2021. DOI: https://doi.org/10.1007/s10796-021-10131-x.
PRADUMAN, Jain; SCHILLING, Josh; KLEIN, Dave. Vignet Inc. Depositante: Potentiators of Antimicrobial and/or Antiviral Agents. WIPO, 2020.
RAHIMZADEH, Mohammad; ATTAR, Abolfazl. A modified deep convolutional neural network for detecting COVID-19 and pneumonia from chest X-ray images based on the concatenation of Xception and ResNet50V2. Informatics in Medicine Unlocked, [s.l.], v. 19, p. 100360, 2020. DOI: https://doi.org/10.1016/j.imu.2020.100360.
RAO, Arni SR Srinivasa; 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. Infection Control & Hospital Epidemiology, [s.l.], v. 41, n. 7, p. 826-830, 2020. DOI: https://doi.org/10.1017/ice.2020.61.
RAPIN, Jérémy; JIA, Li; MASSIAS, Mathurin. Cardiologs Technologies SAS. Depositante: Automatic method to delineate or categorize an electrocardiogram. EUA, US11331034B2, 2022.
SANTUS, Enrico et al. Artificial intelligence–aided precision medicine for COVID-19: strategic areas of research and development. Journal of Medical Internet Research, [s.l.], v. 23, n. 3, p. e22453, 2021. DOI: https://dx.doi.org/10.2196/22453.
STEVANIM, Luiz Felipe et al. Uma vacina para a humanidade: da expectativa à realidade, os esforços para se chegar a uma vacina contra Covid-19 acessível à população. 2020. Disponível em: https://www.arca.fiocruz.br/handle/icict/43683
UNCTAD. Catching technological waves: Innovation with equity. Technology and innovation report 2021. 2021. Disponível em: https://unctad.org/system/files/official-document/tir2020_en.pdf. Acesso em: 1º ago. 2022.
XU, Zhenxing et al. Artificial intelligence for COVID-19: Battling the pandemic with computational intelligence. Intelligent Medicine, [s.l.], 2021. DOI: https://doi.org/10.1016/j.imed.2021.09.001.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Cadernos de Prospecção
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
O autor declara que: - Todos os autores foram nomeados. - Está submetendo o manuscrito com o consentimento dos outros autores. - Caso o trabalho submetido tiver sido contratado por algum empregador, tem o consentimento do referido empregador. - Os autores estão cientes de que é condição de publicação que os manuscritos submetidos a esta revista não tenham sido publicados anteriormente e não sejam submetidos ou publicados simultaneamente em outro periódico sem prévia autorização do Conselho Editorial. - Os autores concordam que o seu artigo ou parte dele possa ser distribuído e/ou reproduzido por qualquer forma, incluindo traduções, desde que sejam citados de modo completo esta revista e os autores do manuscrito. - Revista Cadernos de Prospecção está licenciado com uma Licença Creative Commons Attribution 4.0. Esta licença permite que outros remixem, adaptem e criem a partir do seu trabalho para fins não comerciais, e embora os novos trabalhos tenham de lhe atribuir o devido crédito e não possam ser usados para fins comerciais, os usuários não têm de licenciar esses trabalhos derivados sob os mesmos termos.
Este obra está licenciado com uma Licença Creative Commons Atribuição 4.0 Internacional.
