In this study, UV-VIS spectroscopy was used as a tool for detecting low glucose concentrations in urine. Measurements were performed on artificial urine samples and solutions with 0.1% and 0.2% glucose, covering both normal and pathological thresholds. Among the evaluated models, Random Forest reached 0.887for the 0.1% glucose sample, while Logistic Regression achieved 0.7796 for the 0.2% glucose sample,...

This study presents anoptical fiber sensor for detecting low glucose concentrations in a sample mimicking urine. Our research focused on designing a sensor capable of detecting 0.5% glucose concentrations in artificial urine. Algorithms were applied to analyze and accurately classify the data andidentify the principal components of the collected data. The Random Forest and XGBoostmodel achieved the highest...