Artificial intelligence in acupuncture: A bibliometric study.

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Abstract

This study aimed to provide a panorama of artificial intelligence (AI) in acupuncture by characterizing and visualizing the knowledge structure, hotspots and trends in global scientific publications. Publications were extracted from the Web of Science. Analyses on the number of publications, countries, institutions, authors, co-authorship, co-citation and co-occurrence were conducted. The USA had the highest volume of publications. Harvard University had the most publications among institutions. Dey P was the most productive author, while lczkowski KA was the most referenced author. The Journal of Alternative and Complementary Medicine was the most active journal. The primary topics in this field concerned the use of AI in various aspects of acupuncture. “Machine learning” and “deep learning” were speculated to be potential hotspots in acupuncture-related AI research. In conclusion, research on AI in acupuncture has advanced significantly over the last two decades. The USA and China both contribute significantly to this field. Current research efforts are concentrated on the application of AI in acupuncture. Our findings imply that the use of deep learning and machine learning in acupuncture will remain a focus of research in the coming years.