结核病成像中的人工智能:研究趋势和合作的全球图书识别分析
X B Wei1, N Mohd Norsuddin2, M I Azmi3
1Centre of Diagnostic Imaging, Therapeutic and Investigative Studies (CODTIS), Faculty of Health Sciences, The National University of Malaysia (UKM), 50300 Kuala Lumpur, Malaysia; Department of Imaging, Zunyi Bozhou District People's Hospital, Zunyi 563100, China.
Radiography (London, England : 1995)
|February 13, 2026
概括
结核病 (TB) 成像中的人工智能 (AI) 显示出快速增长,从早期的计算机辅助诊断演变为深度学习应用. 胸部X射线 (CXR) 是查的关键,人工智能在全球范围内提高了结核病检测.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 图书统计学 图书统计学
背景情况:
- 结核病 (TB) 是全球主要的健康威胁,成像对诊断和查至关重要.
- 人工智能 (AI) 越来越多地用于结核病的胸部X射线 (CXR) 和计算机断层扫描 (CT).
- 没有一项文献计量研究绘制出了人工智能在结核病成像中的演变.
研究的目的:
- 综合地绘制人工智能驱动的结核病成像的出版趋势.
- 分析合作,成像模式,技术进化和研究热点.
- 了解人工智能在结核病诊断中的应用轨迹.
主要方法:
- 从Web of Science和Scopus (2000-2025) 中对556篇出版物的图书统计分析.
- 使用CiteSpace和VOSviewer分析趋势,协作和关键词.
- 专注于英语文章和评论.
主要成果:
- 快速的出版增长 (21.2%的复合年增长率),其中印度和中国处于领先地位.
- 胸部X射线 (CXR) 是主要的成像方式.
- 研究经历了三个阶段:CAD,深度学习和临床部署,其中关键领域是机器学习和结核病检测.
结论:
- 结核病成像中的AI已经从早期的CAD迅速发展到深度学习,CXR对查至关重要.
- 未来的研究应该专注于可解释和可泛化的人工智能,以产生全球影响.
- 整合基于人工智能的成像,特别是CXR-AI,可以显著帮助在高负担地区检测结核病.
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