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目的 运用CiteSpace 6.2 R4软件分析人工智能应用于慢性阻塞性肺疾病（COPD）领域国内外研究现状与热点趋势。方法 以“慢性阻塞性肺疾病”“慢阻肺”“人工智能”“chronic obstructive pulmonary disease”“COPD”“深度学习”“机器学习”“artificial intelligence”“deep learning”“machine learning”为主题词，检索中国知网、万方数据知识服务平台、维普网、Web of science核心数据库收录的人工智能应用于COPD领域的相关文献，检索时间为自建库至2025年3月31日。基于CiteSpace 6.2 R4软件对文献进行网络图谱分析。结果 共纳入1 292篇文献，其中中文文献197篇、英文文献1 095篇，发文量整体呈上升趋势。中文期刊《放射学实践》刊载文献数量最多（6篇），英文期刊《American Journal of Respiratory And Critical Care Medicine》刊载文献数量最多（56篇）。英文文献发文量前3名的国家分别为美国、中国、英国，中心性前3名的国家分别为美国、英国、西班牙。中文文献形成199个关键词，19个关键词聚类；英文文献形成446个关键词，27个关键词聚类。中英文共有热点关键词为“慢阻肺”“机器学习”“人工智能”“深度学习”，主要聚类为预测模型、人工智能、体层摄影术、物联网、air pollution、transfer learning、mortality。中英文突现关键词为“声学分析”“慢性阻塞性”“Particulate matter”“Transfer learning”和“Spirometry”。结论 人工智能应用于COPD领域研究热度逐年上升，英文文献发文量整体高于中文文献。当前主要研究热点为基于CT影像、肺功能及呼吸音等数据的风险预测模型搭建、物联网应用、迁移学习、空气污染和病死率。CT影像组学和人工智能的应用最为深入和广泛，国内外研究情况有一定差异。
Abstract：Objective To analyze the current status and trends of the application of artificial intelligence in the field of chronic obstructive pulmonary disease(COPD) both domestically and internationally using CiteSpace 6. 2 R4 software. Methods Using "chronic obstructive pulmonary disease", "COPD", "artificial intelligence", "deep learning" and "machine learning" as the keywords, we retrieved relevant domestic and international literature from databases of CNKI, WanFang, VIP, and Web of Science Core Collection. The retrieval spanned from database inception to March 31, 2025. A network mapping analysis of the literature was conducted using CiteSpace 6. 2 R4 software. Results A total of 1,292 articles(197 Chinese and 1,095 English) were included, showing an overall upward trend in publication volume. Among Chinese journals, "Radiologic Practice" published the most articles(6), while among English journals, the "American Journal of Respiratory and Critical Care Medicine" ranked first(56 articles). The top three countries in English publication volume were the United States(341 articles), China(227 articles), and the United Kingdom(978. 86%). The top three in centrality were the United States(0. 32), the United Kingdom(0. 31), and Spain(0. 20). Chinese literature yielded 199 keywords, 519 connections, and 19 keyword clusters; English literature yielded 446 keywords, 2,377 connections, and 27 keyword clusters. Common hotspots in both languages included "COPD", "machine learning", "artificial intelligence", and "deep learning". The main clusters were predictive models, artificial intelligence, tomography, the Internet of Things(IoT), air pollution, transfer learning, and mortality. Emerging keywords in Chinese literature were "lung cancer", "acoustic analysis", "chronic obstructive", and "pulmonary disease", while those in English literature were "particulate matter", "transfer learning", and "spirometry". Conclusions Research on AI in COPD is rising yearly, with English publications surpassing Chinese. Current hotspots focus on predictive model building based on CT images, pulmonary function, respiratory sounds, etc., IoT applications, transfer learning, air pollution, and mortality. CT imaging and AI applications are well-developed and widely used, showing some differences between domestic and international research.
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基本信息:
DOI：
中图分类号:R563.9;G353.1;TP18
引用信息:
[1]战京燕,陈亚南,翟声平.人工智能用于慢性阻塞性肺疾病领域国内外研究热点与趋势分析[J].山东医药,2025,65(09):19-24+28.
基金信息: