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人工智能驱动的智能手机查急性COPD恶化:加强发展中国家地区的健康公平
Yanbin Gong1, Chi Xu1, Caixia Mo2
1Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong, Hong Kong.
NPJ digital medicine
|November 21, 2025
概括
使用智能手机麦克风的AI系统可以早期检测慢性阻塞性肺部疾病 (AECOPD) 的急性恶化. 这项技术为改善COPD管理提供了具有成本效益的解决方案,特别是在服务不足的地区.
科学领域:
- 人工智能在医学中的应用
- 肺部医学 肺部医学
- 卫生技术评估 卫生技术评估
背景情况:
- 慢性阻塞性肺病 (AECOPD) 的急性恶化是临床关键事件.
- 早期发现AECOPD在初级保健中具有挑战性,特别是在资源有限的环境中.
- 延迟诊断AECOPD有助于患者的不良结果和增加医疗保健负担.
研究的目的:
- 开发和评估基于人工智能的系统,用于使用智能手机麦克风检测AECOPD.
- 评估AI系统的性能和成本效益,以对AECOPD进行选.
- 提供一个可扩展的工具,以提高缺少服务的人群中COPD管理.
主要方法:
- 开发一种人工智能系统,分析标准智能手机麦克风捕获的肺部声音.
- 该系统是为新手用户设计的,不需要主观的患者报告尺度.
- 使用曲线下的面积 (AUC) 和健康经济模型评估系统性能.
主要成果:
- 基于AI的AECOPD检测系统实现了高AUC0.955 (95%CI:0.929-0.976).
- 一个健康经济模型预测,人均潜在净储蓄为456.9元人民币.
- 有90.3%的积极财务回报的概率,表明成本效益.
结论:
- 通过智能手机进行人工智能驱动的听觉,为早期AECOPD检测提供了一个有希望的方法.
- 该系统表现出强大的性能和成本效益,支持其在初级保健中的实施.
- 这项技术可以显著改善COPD管理,并促进在专家获取有限的地区的健康公平.
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