A Bibliometric Analysis of Artificial Intelligence applications during COVID-19 Based on Web of Science (WoS) Database - Algamdi, Abdelmageed (Journal of engineering sciences and information technology, 2022)
This article opens up another analytic method of Artificial Intelligence applications in Light of COVID-19, mainly explaining this binding domain’s current trends and knowledge areas, according to the data analysis of previous studies in this field. The bibliometric study was performed to present new research trends in Artificial Intelligence in light of COVID-19. The data of 1635 studies published in Web of Science were analyzed during the last two years (2020-2021). We achieved the bibliometric analysis using three software CiteSpace, VOSviewer, and KnowledgeMatrix Plus. The findings of bibliometric analysis suggest that there are twelve research clusters in this topic (emerging industry, cross-sectional survey study, emerging technologies, joint position paper, colony predation algorithm, medical worker, deep learning, covid-19 risk prediction, future smart connected communities, supply chain resilience, virtual screening, and k-12 students). The United States, People’s Republic of China, the United Kingdom, India, Saudi Arabia, Italy, Australia, Spain, South Korea, and Canada are the most intriguing countries that investigated this issue during COVID-19, so this study reveals the latest policy trends in Artificial intelligence using bibliometric analysis.