Bibliometric exploration of artificial intelligence applications in healthcare: trends and future directions 10.55131/jphd/2025/230220
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Abstract
This research employs the PRISMA framework to conduct an extensive bibliometric analysis, delving into the dynamic realm of Artificial Intelligence (AI) within the healthcare domain. Spanning the years 2010 to 2023, the study systematically gathers and examines scholarly works to delineate the trends, patterns, and emerging topics about AI's integration into healthcare. A thorough initial screening yields substantial academic articles, conference papers, and reviews, forming the basis for analysis. The examination primarily focuses on quantifying publication patterns, identifying influential authors, institutions, and countries, and mapping the thematic landscape of AI in healthcare. Employing various bibliometric metrics such as publication trends, prolific authors, influential journals, and co-occurrence networks of keywords, the study uncovers the remarkable surge in research centred on AI-driven healthcare. This surge signifies a notable paradigm shift towards harnessing technology for predictive analytics, personalized medicine, and enhanced patient care. Additionally, by leveraging visualization tools like VOSviewer, the study presents informative graphical representations elucidating clusters and associations among keywords, thereby providing deeper insights into the interdisciplinary dimensions of AI in healthcare. This study provides a structured overview of the evolving landscape of AI in healthcare, providing valuable perspectives for researchers, practitioners, and policymakers aiming to harness the potential of AI for advancing healthcare delivery and outcomes. The implications of these findings underscore the transformative potential of AI technologies in revolutionizing healthcare delivery, promoting sustainable healthcare practices, and fostering innovative solutions for future challenges.
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