基于CiteSpace的人工智能在ICU中应用的研究的可视化分析
Visual Analysis of Research on the Application of Artificial Intelligence in ICU Based on CiteSpace
DOI: 10.12677/ns.2026.157237, PDF,    科研立项经费支持
作者: 蔡雪妍:徐州医科大学护理学院,江苏 徐州;陆昌浩, 彭 琳*:海军军医大学第一附属医院重症医学科,上海;宋梦珂, 熊 灿:郑州大学护理与健康学院,河南 郑州
关键词: 人工智能ICU文献计量学数据可视化研究热点Artificial Intelligence ICU Bibliometrics Data Visualization Research Hotspots
摘要: 目的:对人工智能在ICU中应用领域的研究现况、热点及发展趋势进行可视化分析。方法:以中国知网(CNKI)、万方数据库(WanFang Database)、维普(VIP)、WOS等为数据源,检索2000年1月1日~2025年10月31日有关人工智能在ICU中应用研究的文献,采用CiteSpace软件对文献年发文量、发文机构、关键词等进行可视化分析。结果:国内外人工智能在ICU中应用的研究呈现持续增长趋势。英文文献的发文量和中心性均高于中文文献,发文量最多的是哈佛大学(78篇),中心性指数最高的是哈佛大学医学附属机构(0.20)。中文文献发文量排名前10位的机构发文量均低于10,中心性指数均为0。国内研究热点集中于预测模型、危险因素、列线图等方面,“machine learning (机器学习)”“intensive care unit (重症监护室)”“mortality (死亡)”是国外的研究热点。结论:AI作为一门新技术科学,在ICU中的应用已受到广泛关注。国内外人工智能在ICU中应用的研究呈快速增长趋势,我国的研究呈现良好态势,但发文量较少,仍需加强国际合作,深入研究。
Abstract: Objective: This study aims to conduct a visual analysis of the research status hotspots and development trends of artificial intelligence in the field of ICU applications. Method: With CNKI, WanFang Database, VIP and WOS as data sources, retrieve the literature on the application and research of artificial intelligence in ICU from January 1, 2000 to October 9, 2025, and use CiteSpace software to visually analyze the annual volume of literature, issuing countries, institutions, authors, keywords, etc. Results: The applied research of artificial intelligence in ICU at home and abroad shows a continuous growth trend. The volume and centrality of English literature are higher than those of Chinese literature. Harvard University (78 articles) has the highest number of articles, and the highest centrality index is Harvard Medical Affiliate (0.20). The top 10 institutions in the volume of Chinese literature are all below 10, and the centrality index is 0. Domestic research hotspots focus on predictive models, risk factors, line charts, etc., “machine learning”, “intensive care unit” and “mortality” are foreign research hotspots. Point. Conclusion: As a new technology science, the application of AI in ICU has received wide attention. The research on the application of artificial intelligence in ICU at home and abroad is growing rapidly. China’s research is showing a good trend, but the volume of articles is small, and it is still necessary to strengthen international cooperation and in-depth research.
文章引用:蔡雪妍, 陆昌浩, 宋梦珂, 熊灿, 彭琳. 基于CiteSpace的人工智能在ICU中应用的研究的可视化分析[J]. 护理学, 2026, 15(7): 233-246. https://doi.org/10.12677/ns.2026.157237

参考文献

[1] 陈妞, 陈莹, 郭瑾, 等. 人工智能在危重症护理中的应用现状及挑战[J]. 中华急危重症护理杂志, 2022, 3(3): 276-279.
[2] 张茂. 未来智慧ICU的建设[J]. 中华医学信息导报, 2022, 37(6): 16.
[3] Li, Y., Wang, M., Wang, L., Cao, Y., Liu, Y., Zhao, Y., et al. (2024) Advances in the Application of AI Robots in Critical Care: Scoping Review. Journal of Medical Internet Research, 26, e54095.
https://doi.org/10.2196/54095
[4] Liu, J.W. and Huang, L.C. (2008). Detecting and Visualizing Emerging Trends and Transient Patterns in Fuel Cell Scientific Literature. 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing, Dalian, 12-17 October 2008, 11435-11438.
https://doi.org/10.1109/wicom.2008.2660
[5] 邓一, 宋珊珊, 董丽. 基于CiteSpace的我国脑瘫儿童康复护理的可视化分析[J]. 中华现代护理杂志, 2024, 30(7): 943-949.
[6] 汪卓剑, 张岚. 基于CiteSpace的ICU患者疼痛管理研究可视化分析[J]. 中华疼痛学杂志, 2024, 20(6): 905-912.
[7] 唐淑慧, 肖瑛, 席惠君, 等. 基于CiteSpace的军队岛礁医院相关研究热点的可视化分析[J]. 军事护理, 2024, 41(10): 74-77.
[8] 高成菲, 陆小英, 马倩云, 等. 基于CiteSpace的专科护理门诊研究现状与热点的可视化分析[J]. 中华现代护理杂志, 2025, 31(18): 2435-2441.
[9] 郑铭柯, 徐昉. 重症医学临床预测模型的应用研究进展[J]. 现代医药卫生, 2025, 41(12): 2870-2873+2878.
[10] van Beek, S., Nieboer, D., Klimek, M., Stolker, R.J. and Mijderwijk, H. (2024) Development and External Validation of a Clinical Prediction Model for Predicting Quality of Recovery Up to 1 Week after Surgery. Scientific Reports, 14, Article No. 387.
https://doi.org/10.1038/s41598-023-50518-1
[11] Zhu, Y., Zhang, J., Wang, G., Yao, R., Ren, C., Chen, G., et al. (2021) Machine Learning Prediction Models for Mechanically Ventilated Patients: Analyses of the MIMIC-III Database. Frontiers in Medicine, 8, Article ID: 662340.
https://doi.org/10.3389/fmed.2021.662340
[12] 张锏, 张于, 白静, 等. 基于机器学习与SHAP的ICU乳腺癌患者急性肾损伤风险预测[J]. 中国煤炭工业医学杂志, 2025, 28(6): 525-538.
[13] 王敏, 查君敬, 方秀花, 等. 基于机器学习的ICU患者多重耐药菌感染风险预测模型构建[J]. 成都医学院学报, 2026, 21(1): 127-131.
[14] 严慧娜, 刘瑞云, 李颖, 等. 机器学习临床决策支持系统在ICU中应用的研究进展[J]. 护理研究, 2025, 39(7): 1199-1205.
[15] Moazemi, S., Vahdati, S., Li, J., Kalkhoff, S., Castano, L.J.V., Dewitz, B., et al. (2023) Artificial Intelligence for Clinical Decision Support for Monitoring Patients in Cardiovascular ICUs: A Systematic Review. Frontiers in Medicine, 10, Article ID: 1109411.
https://doi.org/10.3389/fmed.2023.1109411
[16] Wang, D., Li, J., Sun, Y., Ding, X., Zhang, X., Liu, S., et al. (2021) A Machine Learning Model for Accurate Prediction of Sepsis in ICU Patients. Frontiers in Public Health, 9, Article ID: 754348.
https://doi.org/10.3389/fpubh.2021.754348
[17] 柏永青, 杨雅萍, 孙九林. 国内外科学数据管理办法研究进展[J]. 农业大数据学报, 2019, 1(3): 4-20.
[18] Berkhout, W.E.M., van Wijngaarden, J.J., Workum, J.D., van de Sande, D., Hilling, D.E., Jung, C., et al. (2025) Operationalization of Artificial Intelligence Applications in the Intensive Care Unit: A Systematic Review. JAMA Network Open, 8, e2522866.
https://doi.org/10.1001/jamanetworkopen.2025.22866
[19] Suresh, V., Singh, K.K., Vaish, E., Gurjar, M., Am, A., Khulbe, Y., et al. (2024) Artificial Intelligence in the Intensive Care Unit: Current Evidence on an Inevitable Future Tool. Cureus (Palo Alto, CA), 16, e59797.
https://doi.org/10.7759/cureus.59797
[20] Cecconi, M., Greco, M., Shickel, B., Angus, D.C., Bailey, H., Bignami, E., et al. (2025) Implementing Artificial Intelligence in Critical Care Medicine: A Consensus of 22. Critical Care, 29, Article No. 290.
https://doi.org/10.1186/s13054-025-05532-2
[21] 郑锐, 季梦婷, 冯雨萱, 等. 诊断类智能化临床决策支持系统应用现状与思考[J]. 上海医药, 2024, 45(9): 3-9+18.
[22] Ahmed, M.I., Spooner, B., Isherwood, J., Lane, M., Orrock, E. and Dennison, A. (2023) A Systematic Review of the Barriers to the Implementation of Artificial Intelligence in Healthcare. Cureus, 15, e46454.
https://doi.org/10.7759/cureus.46454
[23] 徐天宇, 余松轩, 侯冷晨, 等. 数智融合背景下重症医学科发展的机遇、挑战与对策[J]. 海军军医大学学报, 2025, 46(1): 118-122.
[24] 崔芳芳, 李中琳, 何贤英, 等. 医疗人工智能临床应用的伦理思考[J]. 中国医学伦理学, 2025, 38(2): 159-165.
[25] 刘旭东, 李敏香, 徐百超, 等. 人工智能在心脏骤停急救应用中的伦理挑战与对策[J]. 中国急救医学, 2024, 44(11): 985-990.
[26] 国务院关于印发新一代人工智能发展规划的通知[EB/OL]. 2017-07-20.
https://www.gov.cn/zhengce/content/2017-07/20/content_5211996.htm
, 2026-01-09.
[27] 关于印发涉及人的生命科学和医学研究伦理审查办法的通知[EB/OL]. 2023-02-28.
https://www.gov.cn/zhengce/zhengceku/2023-02/28/content_5743658.htm
, 2025-12-07.
[28] 雷芳, 杜亮, 董敏, 等. 基于人工智能的临床决策支持系统早期临床评估的透明化报告[J]. 中国全科医学, 2024, 27(10): 1267-1270.
[29] 翁成杰, 潘向滢, 王金宁, 等. ICU警报管理数字化与智能化的研究进展[J]. 中华急危重症护理杂志, 2025, 6(3): 380-384.
[30] 朱曼晨, 胡春英, 贺银燕, 等. 基于机器学习的重症监护病房脓毒症患者住院病死率预测模型的构建[J]. 中华危重病急救医学, 2023, 35(7): 696-701.