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Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
Published on: October 24, 2019
Artificial Intelligence in Nursing Education: A Bibliometric Analysis
Xiaoyue Yu1,2, Weizhen Wu1, Jun Ni3
1Department of Obstetrics and Gynecology, Department of Nursing, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, Guangdong-HongKong-Macao Greater Bay Area Higher Education Joint Laboratory of Maternal-Fetal Medicine, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China, gzhmc.edu.cn.
Background:
The swift advancement of artificial intelligence (AI) has significantly impacted multiple industries. The prospects of AI within nursing education are especially promising, as it presents avenues for enhancing the preparation of forthcoming nursing practitioners in a constantly changing healthcare landscape.
Methods:
We employed VOSviewer, CiteSpace, and the Bibliometrix R package to effectively visualize the bibliometric findings.
Results:
A total of 430 publications were identified. The predominant sources of these publications were the United States of America and China, while the National University of Singapore emerged as the foremost contributor. The journals that provided the most substantial input in this area included Nurse Education Today and Nurse Education in Practice. Furthermore, keywords showed significant citation bursts and trending topics, such as technology, educational programs, and simulation.
Conclusions:
The results of this investigation offer novel perspectives for scholars who are keen on examining the integration of AI in the training of nursing education.
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