Modeling and innovation using artificial intelligence in accelerating handling the COVID-19 pandemic: A bibliometric study

Abstract

This study aims to analyze previous publications with the theme of modeling and innovation using artificial intelligence in accelerating the handling of COVID-19. The data of this study come from the Scopus database. This study uses VOSviewer to evaluate keywords from 575 publications in the Scopus database with research topics. Next, analysis of Scopus database search results visualizes features and trends of related journals, authors, and themes. This study found that articles on modeling and innovation using artificial intelligence in accelerating the handling of COVID-19 have been published in 267 journals, with the most popular journals being Chaos, Solitons, and Fractals. The results of bibliometric analysis show that there are ten popular journals, with The Lancet Infectious Diseases receiving the most citations. Likewise, in this study there are authors who have the most article documents, namely J.S. Suri with 4 (four) documents, and X. Xu is the most popular author with the most citations. The results of this study show that an AI approach can help in the dissemination of important information around the world while reducing the spread of misinformation about COVID-19. This study suggests that focused, effective, and efficient collaboration, coordination, and harmonization are needed between the central government, local governments, and commercial entities.

Stagnansi Keterpilihan Perempuan dalam Pemilu Indonesia: Sebuah Literature Review

“…There are several stages that must be completed before carrying out bibliometric analysis, including the data search process, bibliographic filtering, cross-checking bibliographic properties, and finally bibliometric analysis (Sadat & Lawelai, 2023). Several tools and websites help visualize the process.…”