Research trends and patterns of artificial intelligence in healthcare using bibliometric analysis

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.