Treffer: Global research landscape on artificial intelligence in arthroplasty: A bibliometric analysis

Title:
Global research landscape on artificial intelligence in arthroplasty: A bibliometric analysis
Contributors:
National Key Research and Development Program of China, National Natural Science Foundation of China, Military Medical Science and Technology Youth Training Project
Source:
DIGITAL HEALTH ; volume 9 ; ISSN 2055-2076 2055-2076
Publisher Information:
SAGE Publications
Publication Year:
2023
Document Type:
Fachzeitschrift article in journal/newspaper
Language:
English
DOI:
10.1177/20552076231184048
Accession Number:
edsbas.4EE48903
Database:
BASE

Weitere Informationen

Background Artificial intelligence (AI) has promising applications in arthroplasty. In response to the knowledge explosion resulting from the rapid growth of publications, we applied bibliometric analysis to explore the research profile and topical trends in this field. Methods The articles and reviews related to AI in arthroplasty were retrieved from 2000 to 2021. The Java-based Citespace, VOSviewer, R software-based Bibiometrix, and an online platform systematically evaluated publications by countries, institutions, authors, journals, references, and keywords. Results A total of 867 publications were included. Over the past 22 years, the number of AI-related publications in the field of arthroplasty has grown exponentially. The United States was the most productive and academically influential country. The Cleveland Clinic was the most prolific institution. Most publications were published in high academic impact journals. However, collaborative networks revealed a lack and imbalance of inter-regional, inter-institutional, and inter-author cooperation. Two emerging research areas represented the development trends: major AI subfields such as machine learning and deep learning, and the other is research related to clinical outcomes. Conclusion AI in arthroplasty is evolving rapidly. Collaboration between different regions and institutions should be strengthened to deepen our understanding further and exert critical implications for decision-making. Predicting clinical outcomes of arthroplasty using novel AI strategies may be a promising application in this field.