Research trends and patterns of artificial intelligence in healthcare using bibliometric analysis
TL;DR
A comprehensive bibliometric analysis of 594 peer-reviewed publications indexed in Scopus between 2012 and April 2024 reveals a marked acceleration in research output after 2018, with the United States, China, and the United Kingdom emerging as dominant contributors and central hubs in international collaboration networks.
Abstract
Artificial intelligence (AI) has increasingly become a central component of healthcare research, yet a systematic understanding of its scholarly evolution remains limited. This study presents a comprehensive bibliometric analysis of 594 peer-reviewed publications indexed in Scopus between 2012 and April 2024, retrieved using a focused title-based search strategy. Using VOSviewer, we examine publication and citation trends, leading contributing countries and institutions, and thematic structures through keyword co-occurrence networks. Results reveal a marked acceleration in research output after 2018, with the United States, China, and the United Kingdom emerging as dominant contributors and central hubs in international collaboration networks. Keyword analysis indicates a strong methodological emphasis on machine learning, deep learning, and medical imaging, while comparatively limited attention is given to ethical, implementation, and equity-related themes. These findings highlight both the rapid growth and the thematic concentration of AI-in-healthcare research, underscoring the need for future studies to address translational and governance challenges alongside technical innovation.