Knowledge graph analysis and visualization of AI technology applied in COVID-19

Area of Science:

• Infectious Diseases and Epidemiology
• Medical Informatics
• Artificial Intelligence in Healthcare

Background:

• The COVID-19 pandemic spurred rapid integration of Artificial Intelligence (AI) into medical research.
• Over 100 AI-focused COVID-19 papers are published monthly, highlighting a significant research surge.
• AI applications span diverse fields including medicine, management, economics, and informatics.

Purpose of the Study:

• To conduct a bibliometric and visual knowledge map analysis of AI applications in COVID-19 research over the past two years.
• To identify key research trends, prolific institutions, and international collaborations in AI for COVID-19.

Main Methods:

• Bibliometric analysis of 1903 publications from the Web of Science (WOS) database.
• Visualization using VOSviewer and CiteSpace tools for multi-dimensional statistical analysis.
• Analysis of publication trends, citation counts, sources, institutions, countries, and collaborations.

Main Results:

• China and the USA are the leading countries in AI applications for COVID-19 research.
• International collaboration among countries and institutions is increasing and yielding impactful results.
• Key research areas include detection, surveillance, risk prediction, therapeutic research, and virus modeling.

Conclusions:

• AI plays a crucial role in advancing COVID-19 research across multiple domains.
• The study highlights the growing importance of international cooperation and identifies key areas for future AI-driven COVID-19 research.
• Identified challenges and limitations provide a roadmap for future research and practical applications of AI in combating COVID-19.