Mapping the Research Landscape of Covid-19 and Artificial Intelligence Using the Lens Database

Authors

Aichetou Mohamed Sidiya, Effat UniversityFollow
Jailan Fouad Aljizawi, Effat UniversityFollow

Abstract

Due to the rapid spread of the COVID-19 pandemic, all countries faced a significant challenge in their efforts to monitor and halt the spread of the virus. Moreover, researchers around the world raced into publishing to get to understand the effects of this pandemic on every aspect of our life whether that was economic, medical, or social. Thus, this research seeks to assess the quality of research on the application of Artificial Intelligence in the Covid-19 pandemic with an emphasis on Saudi Arabia. The research methodology is based on Bibliometric Analysis techniques and VosViewer for various bibliometric visualizations based on the Lens Database, a free database that facilitates the discovery of scholarly as well as patent literature. A total of 15,400 documents were retrieved from the database to identify major emerging themes, removing the duplicates resulted in 14,735 records, and by focusing the search on Saudi Arabia we got 163 results. According to the findings, the primary focus of Artificial Intelligence has been to identify and predict the pandemic proliferation pattern, analyze the COVID-19 virus, and detect its presence in patients. AI was also used to classify and determine the efficiency of drugs and vaccines. The main fields of research are medicine, epidemiology, and computer science. Results show that in Saudi Arabia King Saud University and King Abdulaziz University are among the most active Universities in AI and Covid-19. The research concluded that with the current advancement in AI technology and research, we would be able to deal with future pandemics much more efficiently.

Recommended Citation

Sidiya, Aichetou Mohamed and Aljizawi, Jailan Fouad (2023) "Mapping the Research Landscape of Covid-19 and Artificial Intelligence Using the Lens Database," Effat Undergraduate Research Journal: Vol. 4: Iss. 1, Article 2.
Available at: https://digitalcommons.aaru.edu.jo/eurj/vol4/iss1/2