Classification of glucose-level in deionized water using machine learning models and data pre-processing technique

Accurate monitoring of glucose levels is essential in the field of diabetes detection and prevention to ensure appropriate treatment planning. Conventional blood glucose monitoring methods, although widely used, are intrusive and frequently result in discomfort. This study investigates the use of Ra...

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Veröffentlicht in:	PloS one 2024-12, Vol.19 (12), p.e0311482
Hauptverfasser:	Quang, Tri Ngo, Nguyen Thanh, Tung, Anh, Duc Le, Thi Viet, Huong Pham, Cong, Doanh Sai
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Analysis Biology and Life Sciences Blood Glucose - analysis Blood levels Blood sugar Blood sugar monitoring Care and treatment Classification Computer and Information Sciences Data collection Data mining Deionization Diabetes Diabetes mellitus Diabetes therapy Diagnosis Engineering and Technology Evaluation Glucose Glucose - analysis Glucose monitoring Health aspects Humans Lasers Learning algorithms Machine Learning Medical screening Medicine and Health Sciences Methods Monitoring Monitoring methods Neural networks Physical Sciences Raman spectroscopy Research and Analysis Methods Sample size Sensors Spectroscopic analysis Spectroscopy Spectrum analysis Spectrum Analysis, Raman - methods Support Vector Machine Support vector machines Trees Water Water - chemistry Water analysis Water sampling
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