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• W3204384771 abstract ": COVID-19 is a pandemic initially identified in Wuhan, China, which is caused by a novel coronavirus, also recognized as the Severe Acute Respiratory Syndrome (SARS-nCoV-2). Unlike other coronaviruses, this novel pathogen may cause unusual contagious pain, which results in viral pneumonia, serious heart problems, and even death. Researchers worldwide are continuously striving to develop a cure for this highly infectious disease, yet there are no well-defined absolute treatments available at present. Several vaccination drives using emergency use authorisation vaccines have been held across many countries; however, their long-term efficacy and side-effects studies are yet to be studied. Various analytical and statistical models have been developed, however, their outcome rate is prolonged. Thus, modern science stresses the application of state-of-the-art methods to combat COVID-19. This paper aims to provide a deep insight into the comprehensive literature about AI and AI-driven tools in the battle against the COVID-19 pandemic. The high efficacy of these AI systems can be observed in terms of highly accurate results, i.e., > 95%, as reported in various studies. The extensive literature reviewed in this paper is divided into five sections, each describing the application of AI against COVID-19 viz. COVID-19 prevention, diagnostic, infection spread trend prediction, therapeutic and drug repurposing. The application of Artificial Intelligence (AI) and AI-driven tools are proving to be useful in managing and fighting against the COVID-19 pandemic, especially by analysing the X-Ray and CT-Scan imaging data of infected subjects, infection trend predictions, etc." @default.
• W3204384771 created "2021-10-11" @default.
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• W3204384771 date "2023-01-01" @default.
• W3204384771 modified "2023-10-14" @default.
• W3204384771 title "Artificial Intelligence against COVID-19 Pandemic: A Comprehensive Insight" @default.
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• W3204384771 doi "https://doi.org/10.2174/1573405617666211004115208" @default.
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• W3204384771 hasPublicationYear "2023" @default.
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