ReviewJournal of nursing management2026
Bibliometric Mapping of 40 Years of AI in Nursing: Trends, Collaborations, and Research Hotspots Worldwide.
Review in Journal of nursing management, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Bibliometric Mapping of 40 Years of AI in Nursing: Trends, Collaborations, and Research Hotspots Worldwide.Journal of nursing management · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.