TY - GEN
T1 - Informetric analysis of researches on application of artificial intelligence in COVID-19 prevention and control
AU - Liu, Zhuozhu
AU - Chen, Sijing
AU - Han, Qing
PY - 2021
Y1 - 2021
N2 - 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 categories of researches, high frequency keywords, authors, institutions, journals and countries, and we get conclusions as follows: The analysis of keywords cooccurence shows application of machine learning and deep learning in COVID-19 pandemic diagnosis and prediction. The journal that received the most cites was (Radiology) and the journal that published the most papers was (Journal of Medical Internet Research). USA, India and China have the largest number of published articles. USA, China and UK are most influential countries. 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.
AB - 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 categories of researches, high frequency keywords, authors, institutions, journals and countries, and we get conclusions as follows: The analysis of keywords cooccurence shows application of machine learning and deep learning in COVID-19 pandemic diagnosis and prediction. The journal that received the most cites was (Radiology) and the journal that published the most papers was (Journal of Medical Internet Research). USA, India and China have the largest number of published articles. USA, China and UK are most influential countries. 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.
KW - Artificial Intelligence
KW - COVID-19
KW - Informetric analysis
UR - http://www.scopus.com/inward/record.url?scp=85121511278&partnerID=8YFLogxK
U2 - 10.1117/12.2612150
DO - 10.1117/12.2612150
M3 - Conference proceeding contribution
AN - SCOPUS:85121511278
SN - 9781510650275
T3 - Proceedings of SPIE - The International Society for Optical Engineering
SP - 120760H-1-120760H-6
BT - 2021 International Conference on Image, Video Processing, and Artificial Intelligence
A2 - Zhang, Yudong
PB - SPIE
CY - Bellingham, WA
T2 - 2021 International Conference on Image, Video Processing, and Artificial Intelligence
Y2 - 28 August 2021 through 29 August 2021
ER -