Monitoring Changes in Urine from Diabetic Rats Using ATR-FTIR and Machine Learning

Netcom Pub Date : 2023-07-30 DOI:10.1109/OMN/SBFotonIOPC58971.2023.10230957

Sajid Farooq, Daniella Lúmara Peres, D. C. Caixeta, Cassio Lima, Robinson Sabino Da Silva, D. Zezell

引用次数: 0

Abstract

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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利用ATR-FTIR和机器学习监测糖尿病大鼠尿液变化

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。

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