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用ATR-FTIR光谱检测COVID-19的冷化鼻:基于机器学习的方法

Zubia Shahid¹, Khulla Naseer¹, Irshad Hussain²

¹Department of Biotechnology, Faculty of Biological Sciences, Quaid-i-Azam University, Islamabad, Pakistan.

Biophysical chemistry

|May 17, 2025

概括

淡化总反射率 - 里埃变换红外 (ATR-FTIR) 化鼻的光谱学准确地区分了COVID-19患者与健康个体. 这种光谱法为COVID-19检测提供了强大的和可访问的诊断工具.

科学领域:

生物医学诊断生物医学诊断
频谱学是一种光谱学.
传染病研究传染病研究

背景情况:

由于COVID-19的流行,需要超越标准PCR的先进诊断工具.
基于光谱的诊断为快速和可访问的疾病检测提供了一个有希望的替代方案.
化鼻提供了稳定且适合用于光谱分析的矩阵.

研究的目的:

为了评估减弱总反射率-福里埃变换红外光谱 (ATR-FTIR) 在区分COVID-19阳性和阴性个体之间的疗效,使用冷化鼻样.
在鼻样本中识别可表明COVID-19感染的光谱生物标志物.
评估应用于光谱数据的统计模型的诊断准确性.

主要方法:

使用ATR-FTIR光谱学分析了55个冷化COVID-19阳性和55个阴性鼻样本.
在600-4000厘米-1范围内进行光谱数据预处理和分析.
应用统计方法,包括主要组件分析 (PCA),线性区分分析 (LDA) 和支持矢量机 (SVM) 进行分类.

主要成果:

在健康和感染样本之间观察到显著的光谱变异.
确定了不同的光谱峰值,在COVID-19样本中观察到13个,在负样本中观察到4个.
LDA和SVM模型实现了100%的分类准确性,在内部和外部验证方面表现出高的诊断性能.

结论:

淋化鼻样本是基于FTIR的COVID-19诊断的最佳选择.
与统计分析相结合的ATR-FTIR光谱学为COVID-19检测提供了强大,可访问和高度准确的方法.
这种方法可以成为流行后监测和快速诊断的宝贵工具.

关键词:

在ATR-FTIR中使用.在 COVID-19 疫情中,软化液化化是什么意思机器学习机器学习鼻子抽样鼻子抽样在PCA中,PCA是PCA.频谱学是一种光谱学.

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