利用ATR-FTIR和机器学习监测糖尿病大鼠尿液变化

Sajid Farooq, Daniella Lúmara Peres, D. C. Caixeta, Cassio Lima, Robinson Sabino Da Silva, D. Zezell
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引用次数: 0

摘要

在这里,我们的目标是通过使用ATR-FTIR光谱结合3D判别分析机器学习方法,分析149份尿液光谱样本,包括糖尿病和健康对照组,以更好地表征糖尿病(DM)。结果表明,该模型具有较高的精度,精度接近100%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Monitoring Changes in Urine from Diabetic Rats Using ATR-FTIR and Machine Learning
Here, we aim to better characterize diabetes mellitus (DM) by analyzing 149 urine spectral samples, comprising of diabetes versus healthy control groups employing ATR-FTIR spectroscopy, combined with a 3D discriminant analysis machine learning approach. Our results depict that the model is highly precise with accuracy close to 100%.
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