Informetric Analysis of Researches on Application of Artificial Intelligence in COVID-19 Prevention and Control

The COVID-19 (2019 novel Coronavirus) is the most widespread pandemic infectious disease encountered in human history. Its economic losses and the number of countries involved rank first in the history of human viruses. Since the outbreak of the COVID-19 pandemic around the world, AI has made a great contribution to the prevention and control of the COVID-19 pandemic. In this paper, researches on the application of artificial intelligence in COVID-19 pandemic prevention and control were analyzed by informetric method. 432 papers indexed in Thomson Reuters's Web of Science were studied by the perspectives of keywords co-occurrence and we get conclusions as follows: the analysis of keywords co-occurrence shows application of machine learning and deep learning in COVID-19 pandemic diagnosis and prediction. We also analyzed the review literature on the application of AI in COVID-19 pandemic prevention and control in the Web of Science, and found that these papers specifically can be divided into the following three categories: The first is the application of AI in clinical diagnosis and treatment, the second is the application of AI in the development of anti-epidemic drugs, and the third is the role of AI in the epidemiological research of COVID-19 and the social governance of pandemic prevention and control.