APPLICATION OF ARTIFICIAL INTELLIGENCE IN COMBATING THE COVID-19 PANDEMIC: CURRENT TRENDS AND PROSPECTS. REVIEW

Abstract

Background. The study focuses on the need for effective strategies to address global challenges, such as the COVID19 pandemic, which requires not only medical but also technological responses. In this context, the research aims to analyze issues and assess the potential use of artificial intelligence (AI) in predicting the spread of the virus, taking into account current knowledge and identifying gaps in understanding this field. The aim of this study is to analyze scientific publications dedicated to the use of artificial intelligence in the field of forecasting and prevention of COVID-19 infection. Search strategy. The search for literary sources was conducted in the PubMed database, and the selection of scientific works was based on keywords related to the COVID-19 pandemic and forecasting using artificial intelligence technologies. The search yielded 3,894 publications, extracted on December 27, 2023. Bibliometric analysis was performed using VOSviewer software version 1.6.19, visualizing the interconnections between keywords, identifying clusters of similar terms, and facilitating a deeper understanding of the research topic, trends, and directions in the field of artificial intelligence for combating the COVID-19 pandemic. Exclusion of articles not meeting the keyword criteria was done manually. From the initial pool of 3,894 works, a final set of 23 most relevant publications was selected, reflecting the researched theme and meeting the established search criteria. Conclusions. Contemporary trends and prospects of utilizing models and AI for forecasting COVID-19 outbreaks demonstrate an interdisciplinary approach, encompassing statistical analysis, simulation models, machine learning, and intelligent data analysis. The study emphasizes the importance of data quality, the selection of appropriate algorithms based on country-specific data, and the potential of AI to make a significant contribution to decision-making in public health and pandemic management.