Artificial Intelligence and Big Data for COVID-19 Diagnosis
Integrated Science, ISSN: 2662-947X, Vol: 9, Page: 83-119
2022
- 1Citations
- 15Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Book Chapter Description
The coronavirus disease 2019 (COVID-19) outbreak has given rise to a high number of human deaths as well as chaos in the world’s economic, social, sociological, and health sectors. Controlling an epidemic requires a thorough understanding of the evolution of the epidemic’s features, which may be discovered by gathering and evaluating relevant big data. Big data analytics are essential for obtaining the data needed to make judgments and take precautionary steps. Big data analytics tools are critical for obtaining the information required to make well-informed judgments and take proactive measures. However, assuming the massive data on COVID-19 from different resources, it will be necessary to review the role of big data analysis in controlling COVID-19’s spread, as well as present the main encounters and guidelines of COVID-19 data analysis, and provide a framework for related current applications and frameworks to enable future COVID-19 analysis. Artificial intelligence (AI) technologies are widely used as powerful weapons in the fight against COVID-19. In this chapter, we examine the fundamental scope and contributions of AI in combating COVID-19 from the standpoints of sickness detection and diagnosis. A rundown of the data and technologies available for AI-based COVID-19 research is described. Finally, the major challenges and AI options for fighting COVID-19 are discussed. AI is presently mostly applied in medical image analysis, genomics, and prediction, but it still has a lot of potential in the healthcare sector.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85218753242&origin=inward; http://dx.doi.org/10.1007/978-3-031-11199-0_6; https://link.springer.com/10.1007/978-3-031-11199-0_6; https://dx.doi.org/10.1007/978-3-031-11199-0_6; https://link.springer.com/chapter/10.1007/978-3-031-11199-0_6
Springer Science and Business Media LLC
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