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在印度实施胸部X射线人工智能工具,以加强结核病查:经验教训

Shibu Vijayan¹, Vaishnavi Jondhale², Tripti Pande³

¹Qure.ai, Bangalore, Karnataka, India.

PLOS digital health

|December 7, 2023

概括

人工智能 (AI) 使用胸部X射线 (CXR) 查结核病 (TB) 是有前途的,但现实世界的部署面临挑战. 像qXR这样的AI工具可以在资源有限的环境中将结核病检测率提高15.8%,有助于发现病例.

科学领域:

医疗成像医学成像
医疗保健中的人工智能
公共卫生公共卫生

背景情况:

基于人工智能 (AI) 的结核病 (TB) 胸部X射线 (CXR) 查正在获得吸引力.
人工智能工具的部署面临着重大的现实生活障碍,包括软件安装,工作流集成和网络连接.
资源有限的环境为实施先进的诊断技术带来了独特的挑战.

研究的目的:

评估人工智能软件设备 (qXR) 在资源有限的环境中进行结核病查的运行可行性和可访问性.
识别和解决基于人工智能的结核病查现实生活中的实施挑战.
评估人工智能对结核病例发现在活跃病例发现计划中的影响.

主要方法:

在印度纳格普尔的八个私人CXR实验室中实施了qXR AI软件.
通过非正式提供者和临床病史识别的10,481名可疑结核病患者的查.
放射科医生检测结核病例的比较和CXR图像的AI解释.

主要成果:

人工智能查发现了额外的15.8%的结核病例,这些病例没有被放射科医生标记.
该计划对大量的个人进行了选,证明了大规模应用的潜力.
有关运营可行性和克服实施障碍的策略的关键经验教训.

结论:

基于AI的CXR查,以qXR为例,可以在资源有限的环境中显著提高结核病例的发现.
克服实施挑战对于成功和无地在医疗保健中部署AI工具至关重要.
将人工智能进一步整合到诊断工作流中对于改善全球结核病控制工作至关重要.

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