人工智能用于螺旋测量质量评估:系统性审查
Julia López-Canay1, Manuel Casal-Guisande1,2,3, Cristina Represas-Represas1,3,4
1NeumoVigo I+i Research Group, Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, 36312 Vigo, Spain.
人工智能 (AI) 显示出改善初级保健中螺旋计质量控制的前景. 人工智能工具可以帮助评估测试可接受性和检测错误,但临床实施需要更多的研究.
科学领域:
- 肺部医学 肺部医学
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 螺旋计对于诊断呼吸系统疾病至关重要,但在非专业环境中面临质量控制挑战.
- 人工智能 (AI) 为提高螺旋计可靠性提供了潜在的解决方案.
研究的目的:
- 系统地审查关于人工智能应用在螺旋计质量控制方面的证据.
- 评估人工智能在确保螺旋测量结果可靠性的有效性.
主要方法:
- 在PubMed和IEEE Xplore (2014年 - 2025年6月) 中进行系统的文献搜索.
- 在搜索和数据提取方面遵循PRISMA指南.
- 分析六项包括同行评审的研究.
主要成果:
- 四项研究重点关注机动可接受性/可用性;两项研究关注错误检测.
- 卷积神经网络是最常用的AI模型.
- 三种人工智能模型实现了ROC曲线下的面积> 0.88.8.
结论:
- 人工智能工具显示出对螺旋计质量控制的巨大潜力,有助于验收性评估和错误检测.
- 目前的研究是有限的和异质的,需要更广泛的,多中心验证.
- 需要进一步的研究来证实临床实用性,并促进广泛实施.
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