School of Computer Science, Xianyang Normal University, Xianyang, 712000, Shaanxi, China.
School of Information Engineering, Xizang Minzu University, Xianyang, 712082, Shaanxi, China.
Environ Sci Pollut Res Int. 2022 Apr;29(18):26396-26408. doi: 10.1007/s11356-021-17800-z. Epub 2021 Dec 2.
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.
随着全球冠状病毒病(COVID-19)的爆发,人工智能(AI)技术在 COVID-19 中的应用广泛,成为热门话题。在过去的 2 年中,AI 技术在 COVID-19 中的应用发展迅速,每月发表的相关论文超过 100 篇。在本文中,我们结合文献计量学和可视化知识图谱分析,以 WOS 数据库为样本数据源,应用 VOSviewer 和 CiteSpace 分析工具,对 2 年来(截至今年 7 月底)的 1903 篇文献进行多维统计分析和可视化分析。通过主要年度文章和引文计数、主要出版来源、机构和国家、它们的贡献和合作等几个术语对数据进行分析。自去年以来,COVID-19 的研究急剧增加;特别是结合人工智能技术的相应研究领域正在扩大,如医学、管理、经济学和信息学。中国和美国是 COVID-19 中应用 AI 最活跃的国家,它们对 COVID-19 中应用 AI 做出了重大贡献,因为国家和机构之间的高水平国际合作正在增加,并且更具影响力。此外,我们广泛研究了检测、监测、风险预测、治疗研究、病毒建模和 COVID-19 分析等问题。最后,我们为研究人员和从业者提出了 COVID-19 中应用 AI 的展望挑战和局限性,以促进未来对 COVID-19 中应用 AI 的研究。