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Abstract
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Background and Aims This study aims to use bibliometric methods to identify the contribution of countries, journals, authors, research themes, and emerging trends in artificial intelligence (AI) in pain.
Methods Articles on AI in pain were obtained from the Web of Science database which was accessed on 22 February 2024. TheVOSviewer program was used to visualize trends in research on artificial intelligence in pain.
Results Analyses of 767 original articles revealed that the total number of publications has continually increased over the last 10 years. From 2014 to 2023, it was determined that there was an increase in the number of studies on the use of AI in pain [n:13(2014); n:240(2023)] (figure 1). Scientific Reports (n=31) and Journal of Clinical Medicine are the journals that published the most studies on the use of AI in pain (n=22). The countries with the highest number of studies are the United States (n=174), China (n=131), South Korea (n=88), Germany (n=72), Taiwan (n=59), England (n=54), Canada (n=43), Italy (n=41), Netherlands (n=36), India (n=35), Spain (n=34), Japan (n=33), Australia (n=21), Switzerland (n=24), Saudi Arabia (n=20). In the keyword co-occurrence analysis, 12 clusters were found; machine learning; spine, pain perception, pain, mhealth, pain management, blood sampling, epidural anesthesia, acute coronary syndrome, algorithmic approach, and pain assessment (figure 2).
Years of publications
Keyword co-occurrence analysis
Conclusions The present study evaluated research on acupuncture for pain control using bibliometric methods and revealed current trends in artificial intelligence in pain research, as well as potential future hot spots of research in this field.