Artificial Intelligence in Infectious Disease Research

Area of Science:

• Medical Informatics
• Computational Biology
• Public Health

Background:

• Infectious diseases pose a significant global health threat.
• Artificial intelligence (AI) shows promise in enhancing diagnostic techniques like CT, PET, MRI, and ultrasound.
• The full potential of AI in infectious disease detection and management requires further exploration.

Purpose of the Study:

• To examine global research trends in AI-driven diagnostics for infectious diseases.
• To identify key contributors and thematic shifts in this research area.
• To analyze the geographical distribution and collaboration patterns.

Main Methods:

• Bibliometric analysis of 5465 publications from 2005-2024 from the Web of Science database.
• Keywords included "infectious disease," "communicable disease," "environment," "machine learning," and "artificial intelligence."
• Analysis using pyBibX, bibliometrix, and VOSviewer for trend, author, institution, journal, and thematic mapping.

Main Results:

• The USA leads in publications and citations, followed by China and India.
• Top institutions include the Chinese Academy of Science, University of Oxford, and Harvard Medical School.
• Six key research themes were identified, with machine learning central to diagnostics, epidemiology, imaging, and drug discovery.
• Regional disparities were noted, with underrepresentation from low-income countries.

Conclusions:

• AI is transforming infectious disease research, primarily driven by high-income nations.
• Emerging collaborations in lower-middle-income countries signal a need for equitable AI adoption.
• Global partnerships are essential to overcome disparities in infrastructure, funding, and computational capabilities for AI implementation.