人工智能辅助血糖管理的全球研究趋势：一项文献计量学研究。
Global research trends in AI-assisted blood glucose management: a bibliometric study.
作者信息
Yuan Li, Wang Yangtian, Xing Meiping, Liu Tao, Xiang Dan
机构信息
Department of Endocrinology, Nanjing University Medical School Affiliated Taikang Xianlin Drum Tower Hospital, Nanjing, China.
School of Chinese Medicine, Nanjing University of Chinese Medicine, Nanjing, China.
出版信息
Front Endocrinol (Lausanne). 2025 May 28;16:1579640. doi: 10.3389/fendo.2025.1579640. eCollection 2025.
BACKGROUND
AI-assisted blood glucose management has become a promising method to enhance diabetes care, leveraging technologies like continuous glucose monitoring (CGM) and predictive models. A comprehensive bibliometric analysis is needed to understand the evolving trends in this research area.
METHODS
A bibliometric analysis was performed on 482 articles from the Web of Science Core Collection, focusing on AI in blood glucose management. Data were analyzed using CiteSpace and VOSviewer to explore research trends, influential authors, and global collaborations.
RESULTS
The study revealed a substantial increase in publications, particularly after 2016. Major research clusters included CGM, machine learning algorithms, and predictive modeling. The United States, Italy, and the UK were prominent contributors, with key journals such as leading the field.
CONCLUSION
AI technologies are significantly advancing blood glucose management, especially through machine learning and predictive models. Future research should focus on clinical integration and improving accessibility to enhance patient outcomes.
背景
人工智能辅助的血糖管理已成为一种有前景的改善糖尿病护理的方法，它利用了连续血糖监测（CGM）和预测模型等技术。需要进行全面的文献计量分析，以了解该研究领域的发展趋势。
方法
对来自科学网核心合集的482篇文章进行了文献计量分析，重点是人工智能在血糖管理中的应用。使用CiteSpace和VOSviewer分析数据，以探索研究趋势、有影响力的作者和全球合作情况。
结果
研究显示出版物数量大幅增加，尤其是在2016年之后。主要研究集群包括连续血糖监测、机器学习算法和预测建模。美国、意大利和英国是主要贡献者，诸如 等主要期刊引领该领域。
结论
人工智能技术正在显著推动血糖管理，特别是通过机器学习和预测模型。未来的研究应侧重于临床整合并提高可及性，以改善患者预后。
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