数字健康技术在肺康复领域的研究热点与前沿——基于CiteSpace的知识图谱分析

Research Hotspots and Fronts of Digital Health Technology in Pulmonary Rehabilitation—A Knowledge Graph Analysis Based on CiteSpace

摘要: 目的：基于CiteSpace可视化分析国内数字健康技术工具在肺康复中的研究现状与趋势。方法：系统地检索中国知网数据库自2022年到2026年发表的符合主题的文献，采用NoteExpressV4.X软件对文献进行管理，去重、逐条审查相关性后以Reforworks-CiteSpace格式导出全部题录，通过CiteSpace 6.3.R3软件对关键词、作者及研究机构合作网络进行可视化分析。结果：共纳入有效文献738篇，发文整体呈逐年上升趋势，2020年后进入高速增长阶段；关键词聚类生成肺功能、影像组学、远程医疗、肺疾病、肺癌、生活质量、机械通气、随机森林、呼吸训练9个聚类模块(Q = 0.5085, S = 0.7967)；2024年突现关键词有：生物信息学、肺移植、非小细胞肺癌、风险预测模型、慢性阻塞性肺疾病急性加重；作者和机构合作网络的网络密度分别为：0.0064、0.004。结论：数字健康技术在肺康复中的应用研究已从初步模式探索转向技术深化落地，但跨机构、跨学科协作网络尚未形成，技术迭代速度快于行业规范建设；未来需在创新发展与质量约束间寻求动态平衡，以临床实际获益为核心推动数智化肺康复的标准化落地与高质量发展。

Abstract: Objective: To analyze the research status and trends of domestic digital and intelligent tools in pulmonary rehabilitation based on CiteSpace visualization analysis. Methods: Systematically retrieving literature published in the China National Knowledge Infrastructure (CNKI) database from 2022 to 2026 that aligns with the specified topic. The literature was managed using NoteExpress V4.X software, with deduplication and individual relevance checks performed before exporting all bibliographic records in Reforworks-CiteSpace format. Visual analysis of keywords, authors, and institutional collaboration networks was conducted using CiteSpace 6.3 R3 software. Results: A total of 738 valid articles were included, with the number of publications showing a year-by-year upward trend and entering a phase of rapid growth after 2020. Keyword clustering identified nine clusters: pulmonary function, imagingomics, telemedicine, lung diseases, lung cancer, quality of life, mechanical ventilation, random forest, and respiratory training (Q = 0.5085, S = 0.7967). Emerging keywords in 2024 include bioinformatics, lung transplantation, non-small cell lung cancer, risk prediction models, and acute exacerbations of chronic obstructive pulmonary disease. The network densities for author and institutional collaboration networks were 0.0064 and 0.004, respectively. Conclusion: Research on the application of digital and intelligent tools in pulmonary rehabilitation has progressed from preliminary model exploration to advanced technological implementation. However, cross-institutional and interdisciplinary collaboration networks remain underdeveloped, and technological iteration outpaces the establishment of industry standards. Future efforts must strike a dynamic balance between innovative development and quality constraints, prioritizing clinical benefits to drive standardized implementation and high-quality advancement of digital-intelligent pulmonary rehabilitation.