Intelligent Systems and Novel Coronavirus (COVID-19): A Bibliometric Analysis

Al-Emran, Mostafa; Arpaci, Ibrahim

In late 2019, a novel coronavirus (COVID-19) was determined in Wuhan, China. The newly emerged epidemic has spread rapidly, with an increasing number of confirmed cases worldwide. While intelligent systems have been immensely tested and implemented across a wide range of health problems, the emergence of COVID-19 requires the need to use these systems in detecting, identifying, and preventing its outbreak. By using the bibliometric analysis approach, this research aims to provide a holistic view on the state-of-the-art research concerning intelligent systems and COVID-19 by analyzing the most used keywords, most cited articles and journals, most productive countries and institutions, most cited authors, and the role of intelligent systems during the COVID-19 outbreak. The results indicated that the existing research studies on intelligent systems during the COVID-19 outbreak have mainly concentrated on the use of machine learning algorithms in identifying and diagnosing the potential COVID-19 cases and predicting its extinction time. However, the number of articles published on the role of intelligent systems during COVID-19 pandemic is relatively few, suggesting that research in this field is still in its early stages, and more intensive research is required.