基于Citespace对人工智能在骨创伤研究的可视化分析  

Visualization analysis of artificial intelligence in bone trauma research based on Citespace

作　　者：宋浩然 张玉强 谷娜 智晓东 王伟 Song Haoran;Zhang Yuqiang;Gu Na;Zhi Xiaodong;Wang Wei(Department of Orthopedics,First Affiliated Hospital of Jinzhou Medical University,Jinzhou 121000,Liaoning Province,China;Institute of Osteology,Jinzhou Medical University,Jinzhou 121000,Liaoning Province,China;Department of Radiology,First Affiliated Hospital of Jinzhou Medical University,Jinzhou 121000,Liaoning Province,China)

机构地区：[1]锦州医科大学附属第一医院骨科,辽宁省锦州市121000 [2]锦州医科大学骨外科学研究所,辽宁省锦州市121000 [3]锦州医科大学附属第一医院放射科,辽宁省锦州市121000

出　　处：《中国组织工程研究》2025年第3期493-502,共10页Chinese Journal of Tissue Engineering Research

基　　金：锦州医科大学校企合作基金项目(2020002),项目负责人:王伟;锦州医科大学大学生创新创业训练计划项目(X202210160044),项目负责人:张玉强;锦州市指导性科技计划项目(JZ2023B090),项目负责人:张玉强;锦州医科大学横向课题项目(FSHX202403),项目负责人:王伟。

摘　　要：背景:人工智能在医疗领域的发展日益迅速,在骨创伤领域的应用研究不断增多。文章旨在通过文献计量学分析,分析近年来人工智能在骨创伤领域中的研究热点,并预测未来的研究趋势。目的:总结人工智能技术在骨创伤领域的应用发展历程、研究现状、热点和未来发展趋势,以期为今后的研究提供新的见解。方法:选择Web of Science核心集数据库中,时间跨度设为自建库至2023年8月,检索人工智能、机器学习、深度学习应用于骨创伤相关的文献420篇。通过人工筛选,导出与文章相关的文献共202篇,采用Citespace软件进行国家、机构、被引期刊和引文分析等的合作和关键词的共现等可视化分析。结果与结论:①分析筛选后纳入的202篇文献,总体发文量呈上升趋势,且在未来研究潜力巨大。研究中心性最高和发文量排名第一的国家均为美国。加州大学(美国)是发文量最多的研究机构。②人工智能在骨创伤研究中最常用的前5个关键词是深度学习、人工智能、骨密度、机器学习、诊断,中心性最高的关键词为骨密度,关键词数量最多的为深度学习。③共被引频次前10位的参考文献分别从多个方面介绍了人工智能技术应用于骨创伤领域诊断的可行性研究,其中8篇涉及骨关节损伤与深卷积神经网络,1篇涉及深度学习在CT检查中检测骨质疏松从而预防脆性骨折,1篇通过人工智能识别皮肤纹理变的特征应用于骨的特征性识别的相关性研究。④今后,人工智能的研究热点将主要集中在骨关节创伤和骨质疏松引发的骨折特异性研究上,未来研究趋势主要集中在提升人工智能算法的性能上,使用人工智能新技术对骨损伤进行精准划分和快速高效诊断,尤其是针对复杂和隐匿性骨折的诊断,通过建立有限元分析模型,实现对骨创伤的更加标准化评估。BACKGROUND:The development of artificial intelligence in the medical field is rapidly advancing,with increasing research on its applications in the field of bone trauma.Through bibliometric analysis,this paper analyzed the research hotspots of artificial intelligence in the field of bone trauma in recent years,and predicted the future research trend.OBJECTIVE:To summarize the development history,research status,hot spots,and future development trends of artificial intelligence technology in the field of bone trauma to provide new insights for future research.METHODS:This study selected relevant literature from the Web of Science core database,covering the period from the inception to August 2023,and retrieved 420 articles related to the application of artificial intelligence,machine learning,and deep learning in the field of bone trauma.After manual screening,202 articles related to this article were exported,and Citespace software was used for visual analysis of cooperation of countries,institutions,cited journals,citation analysis,keyword co-occurrence,and other aspects.RESULTS AND CONCLUSION:(1)The overall number of publications from the 202 selected articles showed an upward trend,indicating significant research potential for future studies.The country with the highest centrality and the highest publication volume was the United States.The University of California(USA)was the most prolific research institution.(2)The top five most commonly used keywords in bone trauma research using artificial intelligence were deep learning,artificial intelligence,bone density,machine learning,and diagnosis.The keyword with the highest centrality was bone density,and the keyword with the highest frequency was deep learning.(3)The top 10 most cited reference papers provided comprehensive insights into the feasibility of applying artificial intelligence techniques to the diagnosis of bone trauma from various perspectives.Among them,eight papers focused on bone and joint injuries and deep convolutional neural networks.One paper

关 键 词：人工智能 骨创伤 骨折 机器学习 深度学习 文献计量学 Web of Science 影像诊断 CITESPACE 可视化分析 

分 类 号：R496[医药卫生—康复医学] R318[医药卫生—临床医学] R605