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Knowledge graph analysis and visualization of AI technology applied in COVID-19.
Wu, Zongsheng; Xue, Ru; Shao, Meiyun.
  • Wu Z; School of Computer Science, Xianyang Normal University, Xianyang, 712000, Shaanxi, China. wuzs2005@163.com.
  • Xue R; School of Information Engineering, Xizang Minzu University, Xianyang, 712082, Shaanxi, China.
  • Shao M; School of Information Engineering, Xizang Minzu University, Xianyang, 712082, Shaanxi, China.
Environ Sci Pollut Res Int ; 29(18): 26396-26408, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1549518
ABSTRACT
With the global outbreak of coronavirus disease (COVID-19) all over the world, artificial intelligence (AI) technology is widely used in COVID-19 and has become a hot topic. In recent 2 years, the application of AI technology in COVID-19 has developed rapidly, and more than 100 relevant papers are published every month. In this paper, we combined with the bibliometric and visual knowledge map analysis, used the WOS database as the sample data source, and applied VOSviewer and CiteSpace analysis tools to carry out multi-dimensional statistical analysis and visual analysis about 1903 pieces of literature of recent 2 years (by the end of July this year). The data is analyzed by several terms with the main annual article and citation count, major publication sources, institutions and countries, their contribution and collaboration, etc. Since last year, the research on the COVID-19 has sharply increased; especially the corresponding research fields combined with the AI technology are expanding, such as medicine, management, economics, and informatics. The China and USA are the most prolific countries in AI applied in COVID-19, which have made a significant contribution to AI applied in COVID-19, as the high-level international collaboration of countries and institutions is increasing and more impactful. Moreover, we widely studied the issues detection, surveillance, risk prediction, therapeutic research, virus modeling, and analysis of COVID-19. Finally, we put forward perspective challenges and limits to the application of AI in the COVID-19 for researchers and practitioners to facilitate future research on AI applied in COVID-19.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Artificial Intelligence / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: Environ Sci Pollut Res Int Journal subject: Environmental Health / Toxicology Year: 2022 Document Type: Article Affiliation country: S11356-021-17800-z

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Artificial Intelligence / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: Environ Sci Pollut Res Int Journal subject: Environmental Health / Toxicology Year: 2022 Document Type: Article Affiliation country: S11356-021-17800-z