Use of artificial intelligence in health education: A bibliometric analysis (2018–2025)

Objective: This study aimed to provide an overview of the current state and emerging directions of artificial intelligence research in health education (focusing on patient and public health education rather than professional medical training) through a bibliometric analysis. Methods: Publications indexed in the Web of Science database between 2018 and 2025 that focused on artificial intelligence in health education (encompassing patient education, public health and community health communication) were analysed. 577 articles meeting the inclusion criteria were examined using Biblioshiny and Python to assess annual publication trends, citation patterns, influential journals and authors, collaboration networks, co-citation structures and thematic evolution. Findings were synthesised using descriptive statistics and visual mapping. Results: The findings show a marked increase in artificial intelligence research in health education, particularly after 2023. The literature increasingly concentrates on patient education–related themes, including health literacy, readability, accuracy and the use of conversational agents. Research output and citation impact are dominated by a few countries, notably the USA and China, and are concentrated within a small group of core journals and collaborative networks. Thematic analyses reveal a transition from technology-oriented foundations towards patient- and clinic- applications. Conclusion: Artificial intelligence research in health education now plays a strategic role beyond technical discussions, focusing on patient education and patient–provider health communication. This study maps research trends and highlights areas for future work, especially on the quality, clarity and reliability of artificial intelligence–supported patient information.