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Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
Published on: October 24, 2019
Bibliometric Analysis (2000-2024) of Research on Artificial Intelligence in Nursing
Federica Monaco1, Vincenzo Andretta, Umberto Bellocchio
1Author Affiliations: Department of Critical Care, Anesthesia and Pain Medicine. ASL NA1, Napoli, Italy (Dr Monaco); Department of Medicine, A.O.U. San Giovanni di Dio e Ruggi D'Aragona, U.O.C. Hospital Hygiene and Epidemiology, Salerno, Italy (Prof Andretta); Department of Urology, Istituto Nazionale Tumori-IRCCS, Fondazione Pascale, Naples, Italy (Dr Bellocchio); Department of Medicine, A.O.U. San Giovanni di Dio e Ruggi D'Aragona, U.O.C. Oncology, Salerno, Italy (Dr Cerrone); and Anesthesia and Pain Medicine, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, Baronissi, Italy (Profs Cascella, and Piazza).
Abstract:
We conducted a bibliometrics analysis utilizing the Web of Science database, selecting 1925 articles concerning artificial intelligence (AI) in nursing. The analysis utilized the network visualization tool VOSviewer to explore global collaborations, highlighting prominent roles played by the United States, China, and Japan, as well as institutional partnerships involving Columbia University and Harvard Medical School. Keyword analysis identified prevalent themes and co-citation analysis highlighted influential journals. A notable increase in AI-related publications in nursing was observed over time, reflecting the growing interest in AI in nursing. However, high-quality clinical research and increased scientific collaboration are needed.
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