Bibliometric Mapping of 40 Years of AI in Nursing: Trends, Collaborations, and Research Hotspots Worldwide

Abstract

Background: Artificial intelligence (AI) has increasingly influenced healthcare, yet its adoption in nursing research remains underexplored. Although interest in AI applications, such as robotics, decision support, and machine learning, is growing, a comprehensive bibliometric mapping of global scholarship in nursing remains lacking. Objective: To examine the global trends, intellectual structures, and thematic evolution of AI-related research in nursing from 1984 to 2025 (through May 2025) and to identify key authors, institutions, and research foci. Methods: A systematic search was conducted in the Web of Science Core Collection using predefined title-based keywords ("nurse" OR "nursing") AND ("artificial intelligence" OR "machine learning" OR "deep learning" OR "robotic∗" OR "chatbot∗" OR "neural network∗"). Studies were included if they explicitly addressed nursing practice, management, education, or research applications of AI. Two independent reviewers screened all records by title and abstract to confirm nursing relevance using predefined inclusion and exclusion criteria. This yielded 799 records; after removing duplicates and uncited papers, 530 publications were retained as nursing-related. Bibliometric analysis employed performance and science-mapping techniques via VOSviewer and Biblioshiny. Indicators included publication trends, citation distributions, keyword co-occurrence, authorship patterns, and collaborations. Results: The number of publications increased substantially after 2018, with the United States, China, and the United Kingdom being the most productive countries. Dominant research themes included robotics in elder care, clinical decision support systems, and nursing education enhanced by AI tools. Coauthorship analysis revealed limited international collaboration, and keyword mapping identified "robotics," "machine learning," and "nursing education" as leading focal points. Conclusions: Despite decades of development, AI remains an emerging and underutilized area within nursing research. The rapid growth of publications in recent years signals expanding interest, yet the field lacks consolidated efforts and cohesive global collaboration. Greater interdisciplinary and international engagement is needed to accelerate innovation.

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