Computer intelligence against pandemics: Tools and methods to face new strains of COVID-19
- Authors
- Bhattacharyya, S.[Bhattacharyya, Siddhartha]; Banerjee, J.S.[Banerjee, Jyoti Sekhar]; Gorbachev, S.[Gorbachev, Sergey]; Muhammad, K.[Muhammad, Khan]; Koeppen, M.[Koeppen, Mario]
- Issue Date
- 7-Aug-2023
- Publisher
- De Gruyter
- Keywords
- Big Data; Epidemiologie; Künstliche Intelligenz; Maschinelles Lernen
- Citation
- Computer Intelligence Against Pandemics: Tools and Methods to Face New Strains of COVID-19, pp.1 - 359
- Indexed
- SCOPUS
- Journal Title
- Computer Intelligence Against Pandemics: Tools and Methods to Face New Strains of COVID-19
- Start Page
- 1
- End Page
- 359
- URI
- https://scholarx.skku.edu/handle/2021.sw.skku/107895
- DOI
- 10.1515/9783110767681
- ISSN
- 0000-0000
- Abstract
- This book introduces the most recent research and innovative developments regarding the new strains of COVID-19. While medical and natural sciences have been working instantly on deriving solutions and trying to protect humankind against such virus types, there is also a great focus on technological developments for improving the mechanism - momentum of science for effective and efficient solutions. At this point, computational intelligence is the most powerful tools for researchers to fight against COVID-19. Thanks to instant data-analyze and predictive techniques by computational intelligence, it is possible to get positive results and introduce revolutionary solutions against related medical diseases. By running capabilities - resources for rising the computational intelligence, technological fields like Artificial Intelligence (with Machine / Deep Learning), Data Mining, Applied Mathematics are essential components for processing data, recognizing patterns, modelling new techniques and improving the advantages of the computational intelligence more. Nowadays, there is a great interest in the application potentials of computational intelligence to be an effective approach for taking humankind more step away, after COVID-19 and before pandemics similar to the COVID-19 many appear. © 2023 Walter de Gruyter GmbH, Berlin/Boston. All rights reserved.
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- There are no files associated with this item.
- Appears in
Collections - Computing and Informatics > Convergence > 1. Journal Articles

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