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Machine Learning Approaches in Deal with the COVID-19, Comprehensive Study
1st International Conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021 ; 107:17815-17827, 2022.
Article in English | Scopus | ID: covidwho-1950333
ABSTRACT
The novel Covid illness (COVID-19) has spread more than 219 nations on the globe as a pandemic, making disturbing impacts on medical care, financial conditions, and global connections. The primary goal of the review is to give the Artificial Intelligence's technological aspect and other applicable innovations and their suggestions for standing up to COVID-19 and prevention of the pandemic's frightful impacts. This article presents various approaches with AI moves toward that have huge contribution in the medical service fields, then, at that point, features and sorts their applications in facing Corona virus, like identification and finding, information examination and treatment methods, exploration and medication improvement, social control and benefits, and the expectation of outbreaks. The review tends to the connection between the innovations and the pandemics just as the expected effects of innovation in medical care with the presentation of AI and normal language processing devices. It is usual that this exhaustive review will uphold specialists in demonstrating medical services frameworks and drive further investigations in cutting edge innovations. At last, we conclude that enticing simulated artificial intelligence techniques, probabilistic models, as well as supervised learning are needed to handle future pandemic difficulties. © The Electrochemical Society
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 1st International Conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 1st International Conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021 Year: 2022 Document Type: Article