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An enhanced glucose analysis method based on comprehensive pre-processing methods and multi-feature values-based machine learning

delete2025-07-08
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PRE
AI
R
Ruotong Chen
F
Fang Song
Y
Yang Liu
郑
郑传涛 (Chuantao Zheng)
H
Hengliang Zhu
M
Mingquan Pi
Y
Yue Yang
Y
Yiding Wang
姜秀娥 cover
姜秀娥 (Xiue Jiang)
DOI：10.1016/j.infrared.2025.106008delete
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Abstract

Abstract

En 中文
• Comprehensive discussion on pre-processing methods include background correction and noise elimination algorithms is present. • Four peak heights and four calculated peak heights were jointly selected as feature values for different regression methods. • The RMSE and the R2 of the model are 5.50 mg/dL and 0.999, which has obvious advantages compared with other glucose analysis. • Experiment results of the mixed glucose solution demonstrated the universality and robustness of this method.

Journal

I
Infrared Physics and Technology
IF:
3.4
Papers:
5.8K
Citations:
1.2W

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No organization information available