Silver nanoclusters based glucose biosensors for efficient diagnosis of diabetes mellitus through machine learning approach
Author:
Publisher
AIP Publishing
Link
http://aip.scitation.org/doi/pdf/10.1063/5.0128453
Reference33 articles.
1. An overview on the exponential growth of non-invasive diagnosis of diabetes mellitus from exhaled breath by nanostructured metal oxide Chemi-resistive gas sensors and μ-preconcentrator
2. Socio-economic demands and challenges for non-invasive disease diagnosis through a portable breathalyzer by the incorporation of 2D nanosheets and SMO nanocomposites
3. A breathalyzer for the assessment of chronic kidney disease patients’ breathprint: Breath flow dynamic simulation on the measurement chamber and experimental investigation
4. Naked Eye Detection of Glucose in Urine Using Glucose Oxidase Immobilized Gold Nanoparticles
5. Colorimetric Detection of Urine Glucose Based ZnFe2O4 Magnetic Nanoparticles
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