Objective To analyze the current status, hot spots, and trends of artificial intelligence (AI) in clinical nutrition in the past decade using bibliometric methods.

Methods A systematic search was conducted in the Web of Science Core Collection to identify English-language literature on the application of AI in clinical nutrition. The search period was set from January 1, 2015 to December 31, 2024. CiteSpace 6.4.R1 software was used to conduct visual data analysis of the included literature, covering annual publication volume, authors, countries (regions), keywords, and citation information.

Results A total of 355 articles were included (279 original researchs and 76 reviews). The overall number of publications showed an upward trend, with a particularly sharp increase in 2024. The United States and China were the top two countries in terms of publication volume. The two authors with the highest number of publications (five articles) are both researchers at the University of Valencia in Spain. After excluding the search terms, the top 5 effective high-frequency keywords were health, risk, impact, precision nutrition, and obesity. The results of keyword clustering indicated that dietary assessment, disease nutrition management, and personalized nutrition guidance were the research hotspots in this field.

Conclusion The research on the application of AI in clinical nutrition has been increasing year by year. AI has been widely applied in screening, assessment, diagnosis, and patient education in clinical nutrition, with remarkable effects. In the future, it is necessary to further strengthen the optimization and customized management of AI models to better promote the precise application of AI in clinical nutrition.

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