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首页> 外文期刊>Journal of breath research >Statistical analysis of MCC-IMS data for two group comparisons-an exemplary study on two devices
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Statistical analysis of MCC-IMS data for two group comparisons-an exemplary study on two devices

机译:两个组比较的MCC-IMS数据统计分析 - 两个设备的示例性研究

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摘要

The Multi-capillary-column-Ion-mobility-spectrometry (MCC-IMS) technology for measuring breath gas can be used for distinguishing between healthy and diseased subjects or between different types of diseases. The statistical methods for classifying the corresponding breath samples typically neglects potential confounding clinical and technical variables, reducing both accuracy and generalizability of the results. Especially measuring samples on different technical devices can heavily influence the results.Weconducted a controlled breath gas study including 49 healthy volunteers to evaluate the effect of the variables sex, smoking habits and technical device. Every person was measured twice, once before and once after consuming a glass of orange juice. The two measurements were obtained on two different devices. The evaluation of the MCC-IMS data regarding metabolite detection was performed once using the software VisualNow, which requires manual interaction, and once using the fully automated algorithm SGLTR-DBSCAN. Wepresent statistical solutions, peak alignment and scaling, to adjust for the different devices. For the other potential confounders sex and smoking, in our study no significant influence was identified.
机译:用于测量呼吸气体的多毛细管柱离子迁移率 - 光谱(MCC-IMS)技术可用于区分健康和患病受试者或不同类型的疾病之间。对相应的呼吸样本进行分类的统计方法通常会忽略潜在的混淆临床和技术变量,降低了结果的精度和概括性。特别是在不同技术设备上测量样品可以严重影响结果。导电一种受控的呼吸气体研究,包括49个健康的志愿者,以评估变量性行为,吸烟习惯和技术装置的影响。每人都被测量了两次,一次曾经在烘干一杯橙汁后一次。在两种不同的设备上获得了两种测量。 MCC-IMS数据的评估一次使用软件VisualNow执行一次,需要手动交互,以及一次使用全自动算法SGLTR-DBSCAN。 Wepresent统计解决方案,峰值对齐和缩放,用于调整不同的设备。对于其他潜在的混乱性和吸烟,在我们的研究中,没有发现显着影响。

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