AIMC Topic: Glycosuria
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Utilizing machine learning algorithms for precise discrimination of glycosuria in fluorescence spectroscopic data.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Jun 1, 2024
Fluorescence spectroscopy coupled with a random forest machine learning algorithm offers a promising non-invasive approach for diagnosing glycosuria, a condition characterized by excess sugar in the urine of diabetic patients. This study investigated...
Non-invasive Characterization of Glycosuria and Identification of Biomarkers in Diabetic Urine Using Fluorescence Spectroscopy and Machine Learning Algorithm.
Journal of fluorescence
Aug 3, 2023
The current study presents a steadfast, simple, and efficient approach for the non-invasive determination of glycosuria of diabetes mellitus using fluorescence spectroscopy. A Xenon arc lamp emitting light in the range of 200-950 nm was used as an ex...
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