Artificial Intelligence in General Practice: A Bibliometric Analysis

To analyze the current status, research hotspots, and evolving trends in the application of artificial intelligence (AI) in general practice over the past two decades using bibliometric methods, thereby providing insights for future research.

A systematic search was conducted in the Web of Science Core Collection (WoSCC) to identify English-language literature on AI applications in general practice published between January 1, 2004, and December 31, 2024. VOSviewer 1.6.19 was used for co-occurrence analysis of countries/regions (≥5 publications) and authors (≥3 publications), while Scimago Graphica 1.0.46 was employed to visualize collaboration networks among countries/regions. CiteSpace 6.2.R2 was utilized for institutional co-occurrence analysis (≥5 publications), keyword co-occurrence, and clustering analysis.

A total of 394 relevant articles were included (307 original research articles and 87 reviews). The annual publication output showed a gradual increase, with a notable surge after 2018. The United States and the United Kingdom ranked first in terms of publication volume (81 articles, 20.56%) and total citations (2077 citations), respectively. The University of London was the most prolific institution (20 articles, 5.08%), while Kueper from Western University was the most productive author (6 articles, 1.52%). Journal of Medical Internet Research had the highest number of publications (12 articles, 3.05%) and citations (317 citations) in this field. High-frequency keywords included "diagnosis" (31 occurrences), "management" (29), "risk" (28), "electronic health records" (24), and "care" (23), which were categorized into 7 clusters and further summarized into 4 major research themes. AI applications in health management, diagnostic assistance, and general practitioner training emerged as core research areas, while technological acceptability remained a key challenge.

AI technologies are being progressively integrated into general practice, shifting from fulfilling basic functional needs toward enhancing personalized and intelligent healthcare experiences. Future research should focus on improving AI acceptance among general practitioners and patients through strengthened international and institutional collaboration.