Machine Learning Methods of Regression for Plasmonic Nanoantenna Glucose Sensing

The measurement and quantification of glucose concentrations is a field of major interest, whether motivated by potential clinical applications or as a prime example of biosensing in basic research. In recent years, optical sensing methods have emerged as promising glucose measurement techniques in...

Full description

Saved in:

Bibliographic Details
Published in:	Sensors (Basel, Switzerland) Vol. 22; no. 1; p. 7
Main Authors:	Corcione, Emilio, Pfezer, Diana, Hentschel, Mario, Giessen, Harald, Tarín, Cristina
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 21.12.2021 MDPI
Subjects:	Algorithms Aqueous solutions artificial neural network Fructose Glucose glucose sensing Inverse problems Machine Learning Parameter identification Physical properties Process controls Regression analysis sensor calibration Sensors Spectrophotometry, Infrared Spectrum analysis surface-enhanced infrared absorption spectroscopy artificial neural network surface-enhanced infrared absorption spectroscopy regression analysis Gaussian process regression machine learning glucose sensing sensor calibration
ISSN:	1424-8220, 1424-8220
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!