在初级保健中验证人工智能螺旋计诊断支持软件:一个盲目的诊断准确性研究
Anthony Sunjaya1,2, George D Edwards2, Jennifer Harvey2
1The George Institute for Global Health, UNSW Sydney and Imperial College London, Sydney, NSW, Australia.
ERJ open research
|October 1, 2025
概括
人工智能 (AI) 软件在识别慢性阻塞性肺部疾病 (COPD) 时显示出高准确度. 虽然对COPD有效,但AI对其他慢性呼吸道疾病的表现不那么准确.
科学领域:
- 医疗信息学 医疗信息学
- 肺部病理学 肺部病理学
- 人工智能的人工智能
背景情况:
- 初级保健螺旋计对于诊断呼吸系统疾病至关重要.
- 精确解释螺旋测量数据可能是具有挑战性的.
- 人工智能 (AI) 提供了提高诊断准确性的潜力.
研究的目的:
- 评估AI软件在识别COPD和其他慢性呼吸道疾病时的辨别精度,使用初级保健螺旋计数据.
- 将基于人工智能的诊断与专家肺病学家的共识进行比较.
主要方法:
- 一项使用1113名患者的回顾性初级保健螺旋计数据的诊断研究.
- 人工智能软件 (监督随机森林机器学习) 解释了原始螺旋测量和人口统计数据用于索引诊断.
- 专家肺病学家通过审查全面的医疗记录来建立参考诊断.
主要成果:
- 在COPD检测方面,AI获得了高准确度 (85.4%),灵敏度为84.0%和特异性为86.8% (AUC=0.914).
- 人工智能在间歇性肺病 (AUC=0.900) 和喘 (AUC=0.814) 中表现强.
- 与COPD相比,AI软件在其他慢性呼吸道疾病类别中表现不那么有效.
结论:
- 人工智能软件在初级保健机构中对COPD诊断具有高度敏感性和特异性.
- 人工智能可以作为一个有价值的工具来支持准确的COPD诊断.
- 对于诊断其他慢性呼吸道疾病,人工智能性能不那么强大.
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