A Bibliometric Analysis on the Impact of Machine Learning and Deep Learning Models on COVID -19 in a Workplace

John W. Kasubi, Lazaro A. Kisumbe & Mashala, L. Yusuph
Local Government Training Institute, Dodoma, Tanzania
Email: johnkasubi7@gmail.com

Abstract: The study focused on assessing the impacts of Artificial Intelligence (AI) through Machine Learning (ML) and Deep Learning (DL) modes in combating the COVID-19 pandemic. This study performed a systematic literature review by analyzing articles published between 2020 and 2023 using VOSviewer (version 1.6.18), MS Excel, SPSS, and the PRISMA 2020 statement. The result shows that the research began in 2020 with 105(8%) articles and increased to 480(35%) articles by 2021, in year 2022 a remarkable increase occurred to 622 (46%) publications. The publication trend declined from 46% in the year 2022 to 11% in the year 2023, this might be due to the decrease of pandemic infections. The study includes only the review of the research articles published from 2020 to 2023 and indexed in the Scopus database. The study has explored the impacts of ML and DL models in combating COVID-19 pandemic; that encompasses a rapid and adaptive response to the urgent needs of the pandemic, the discovery of disease and treatment. The study helps society to improve efficiency, enhanced convenience, and innovative solutions across various sectors, such as the ability to react to health emergencies, examine the healthcare and disease management methods. The study provides a remarkable contribution of AI in addressing the Covid-19 pandemic in work a work place and it has been used to monitor and manage the pandemic on a global scale. In addition, the study contributes to understanding the recent growth statistics of global publications that address COVID-19 pandemic.