High-precision prediction of blood glucose concentration utilizing Fourier transform Raman spectroscopy and an ensemble machine learning algorithm
Authors:
- 20 July 2023
- journal article
- research article
- Published by Elsevier in Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy
- Vol. 303, 123176
Abstract
No abstract availableKeywords
Funding Information
- National Natural Science Foundation of China (NFSC 11404054)
- National Natural Science Foundation of China (61601104)
- Fundamental Research Funds for the Central Universities (IEC/NSFC/201078)
- Fundamental Research Funds for the Central Universities (2023GFZD002)
- Natural Science Foundation of Hebei Province (F2019501025)
- Natural Science Foundation of Hebei Province (F2020501040)
- Royal Society
- National University's Basic Research Foundation of China
This publication has 42 references indexed in Scilit:
- Comparison of extreme learning machine models for gasoline octane number forecasting by near-infrared spectra analysisOptik, 2020
- A Noninvasive Accurate Measurement of Blood Glucose Levels with Raman Spectroscopy of Blood in MicrovesselsMolecules, 2019
- Application of BP Neural Network Ensemble Model Based on Bagging AlgorithmInternational Journal of Machine Learning and Computing, 2019
- The Progress of Glucose Monitoring—A Review of Invasive to Minimally and Non-Invasive Techniques, Devices and SensorsSensors, 2019
- Non-invasive monitoring of blood glucose using optical methods for skin spectroscopy—opportunities and recent advancesAnalytical and Bioanalytical Chemistry, 2018
- Spectral quantitative analysis of complex samples based on the extreme learning machineAnalytical Methods, 2016
- Selective neural network ensembles in reinforcement learning: Taking the advantage of many agentsNeurocomputing, 2015
- Extreme learning machine: algorithm, theory and applicationsArtificial Intelligence Review, 2013
- A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithmJournal of Global Optimization, 2007
- Extreme learning machine: Theory and applicationsNeurocomputing, 2006