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Scientific paper - Review paper
Application of Artificial Intelligence-Based Regression Methods in the Problem of COVID-19 Spread Prediction: A Systematic Review
International Journal of Environmental Research and Public Health, 18 (2021), 8; 4287. https://doi.org/10.3390/ijerph18084287
Musulin, Jelena; Baressi Šegota, Sandi; Štifanić, Daniel; Lorencin, Ivan; Anđelić, Nikola; Šušteršič, Tijana; Blagojević, Anđela; Filipović, Nenad; Ćabov, Tomislav; Markova-Car, Elitza

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Musulin, J., Baressi Šegota, S., Štifanić, D., Lorencin, I., Anđelić, N., Šušteršič, T. ... Markova Car, E. (2021). Application of Artificial Intelligence-Based Regression Methods in the Problem of COVID-19 Spread Prediction: A Systematic Review. International Journal of Environmental Research and Public Health, 18. (8). doi: 10.3390/ijerph18084287

Musulin, Jelena, et al. "Application of Artificial Intelligence-Based Regression Methods in the Problem of COVID-19 Spread Prediction: A Systematic Review." International Journal of Environmental Research and Public Health, vol. 18, no. 8, 2021. https://doi.org/10.3390/ijerph18084287

Musulin, Jelena, Sandi Baressi Šegota, Daniel Štifanić, Ivan Lorencin, Nikola Anđelić, Tijana Šušteršič, Anđela Blagojević, Nenad Filipović, Tomislav Ćabov and Elitza Markova Car. "Application of Artificial Intelligence-Based Regression Methods in the Problem of COVID-19 Spread Prediction: A Systematic Review." International Journal of Environmental Research and Public Health 18, no. 8 (2021). https://doi.org/10.3390/ijerph18084287

Musulin, J., et al. (2021) 'Application of Artificial Intelligence-Based Regression Methods in the Problem of COVID-19 Spread Prediction: A Systematic Review', International Journal of Environmental Research and Public Health, 18(8). doi: 10.3390/ijerph18084287

Musulin J, Baressi Šegota S, Štifanić D, Lorencin I, Anđelić N, Šušteršič T, and sur.. Application of Artificial Intelligence-Based Regression Methods in the Problem of COVID-19 Spread Prediction: A Systematic Review. International Journal of Environmental Research and Public Health [Internet]. 2021 April 18 [cited 2024 December 24];18(8). doi: 10.3390/ijerph18084287

J. Musulin, et al., "Application of Artificial Intelligence-Based Regression Methods in the Problem of COVID-19 Spread Prediction: A Systematic Review", International Journal of Environmental Research and Public Health, vol. 18, no. 8, April 2021. [Online]. Available at: https://urn.nsk.hr/urn:nbn:hr:271:294352. [Accessed: 24 December 2024]

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Metadata
Title (english)Application of Artificial Intelligence-Based Regression Methods in the Problem of COVID-19 Spread Prediction: A Systematic Review
AuthorJelena Musulin
AuthorSandi Baressi Šegota
AuthorDaniel Štifanić
AuthorIvan Lorencin
AuthorNikola Anđelić
AuthorTijana Šušteršič
AuthorAnđela Blagojević
AuthorNenad Filipović
AuthorTomislav Ćabov
AuthorElitza Markova-Car
Author's institutionUniversity of Rijeka
(Faculty of Dental Medicine)
Scientific / art field,
discipline and subdiscipline		INTERDISCIPLINARY AREAS OF KNOWLEDGE
Biotechnology in Biomedicine (natural science, biomedicine and healthcare, bioethics area
Abstract (english)
COVID-19 is one of the greatest challenges humanity has faced recently, forcing a change in the daily lives of billions of people worldwide. Therefore, many efforts have been made by researchers across the globe in the attempt of determining the models of COVID-19 spread. The objectives of this review are to analyze some of the open-access datasets mostly used in research in the field of COVID-19 regression modeling as well as present current literature based on Artificial Intelligence (AI) methods for regression tasks, like disease spread. Moreover, we discuss the applicability of Machine Learning (ML) and Evolutionary Computing (EC) methods that have focused on regressing epidemiology curves of COVID-19, and provide an overview of the usefulness of existing models in specific areas. An electronic literature search of the various databases was conducted to develop a comprehensive review of the latest AI-based approaches for modeling the spread of COVID-19. Finally, a conclusion is drawn from the observation of reviewed papers that AI-based algorithms have a clear application in COVID-19 epidemiological spread modeling and may be a crucial tool in the combat against coming pandemics.
Keywords (english)
Languageenglish
Publication typeScientific paper - Review paper
Publication statusPublished
Peer reviewPeer review - international
Publication versionPublished version
Journal titleInternational Journal of Environmental Research and Public Health
Numberingvol. 18, no. 8, 4287
e-ISSN1660-4601
DOIhttps://doi.org/10.3390/ijerph18084287
URN:NBNurn:nbn:hr:271:294352
Publication2021-04-18
Document URLhttps://www.mdpi.com/1660-4601/18/8/4287
Type of resourceText
Access conditionsOpen access
Terms of useLicence Attribution 4.0 International (CC BY 4.0) icon
Created on2023-01-20 10:34:19