人工智能在营养管理领域研究热点的可视化分析OA

[Objective]The objective of this study was to analyze the research status,hotspots,and frontiers of artificial intelligence(AI)in the field of nutrition management in China and globally,and to provide a reference for future research.[Method]A literature analysis was conducted using the visualization software CiteSpace 6.4.R1.We retrieved relevant publications on AI in nutrition management from the CNKI,Wanfang,Weipu,and Web of Science Core Collection databases from their inception until August 1,2025.[Result]A total of 87 Chinese and 113 English publications were included.Although the overall publication output remains relatively low,the number of studies on AI in nutrition management has been increasing.The United States was the leading contributor with 29 publications.Research hotspots primarily focus on AI applications in recommendation systems,dietary assessment,and diet management.Key research frontiers include nutrition management,dietary assessment,knowledge graphs,and machine learning.Emerging trends point towards nutritional status monitoring and personalized nutrition recommendations.[Conclusion]Research on AI in nutrition management is expanding.To foster further development,future research in China should focus on addressing domestic needs while engaging with global frontiers.Enhanced interdisciplinary and international collaboration is recommended to bolster China's impact and accelerate the application of AI in this field.