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从呼出的呼吸中检测到COVID-19的检测
Nicolò Bellarmino1, Riccardo Cantoro2, Michele Castelluzzo3
1Politecnico di Torino, Torino, Italy. nicolo.bellarmino@polito.it.
Scientific reports
|October 6, 2024
概括
一个新的,非侵入性的COVID-19检测系统使用呼气分析. 这种快速呼吸测试的准确性与PCR和抗原测试相提并论,用于识别SARS-CoV-2感染.
科学领域:
- 生物医学工程 生物医学工程
- 传染病诊断 传染病诊断 传染病诊断
- 分析化学 分析化学
背景情况:
- 由于COVID-19的流行,需要快速开发诊断工具.
- 像PCR和抗原测试这样的现有方法在速度和侵入性方面存在局限性.
- 监测和降低感染率仍然是关键的公共卫生优先事项.
研究的目的:
- 引入一种新的,具有成本效益的,非侵入性的COVID-19检测系统.
- 评估SARS-CoV-2的基于呼吸的诊断系统的性能.
- 探索机器学习在分析呼吸质谱以检测疾病方面的潜力.
主要方法:
- 使用微/纳米采样装置与高精度光谱仪相结合,分析呼出的呼吸质谱 (10-351 m/z).
- 采用定制软件算法用于原始光谱处理和数据增强.
- 应用最先进的机器学习算法来对COVID-19病例进行分类.
主要成果:
- 该系统在一个不受控制的临床试验 (302名受试者) 中表现出高性能.
- 实现了95%的准确性,94%的回忆力,96%的特异性和92%的F1得分.
- 性能与传统的聚合酶连锁反应和抗原测试相当.
结论:
- 拟议的呼吸分析系统为COVID-19检测提供了一个快速和非侵入性的替代方案.
- 这项技术有可能为例行查和疫情应对做出重大贡献.
- 进一步开发可以提高未来公共卫生紧急情况的能力.
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