Non-invasive prediction of blood glucose trends during hypoglycemia-Reference-Cited by-同舟云学术

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Non-invasive prediction of blood glucose trends during hypoglycemia

Published:2019-04 Issue: Volume:1052 Page:37-48
ISSN:0003-2670
Container-title:Analytica Chimica Acta
language:en
Short-container-title:Analytica Chimica Acta

Author:

Tronstad Christian,Elvebakk Ole,Staal Odd Martin,Kalvøy Håvard,Høgetveit Jan Olav,Jenssen Trond Geir,Birkeland Kåre Inge,Martinsen Ørjan G.

Funder

Research Council of Norway

South-Eastern Norway Regional Health Authority

Norwegian Diabetes Association

Simon K Fougners

Publisher

Elsevier BV

Subject

Spectroscopy,Environmental Chemistry,Biochemistry,Analytical Chemistry

Reference43 articles.

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2. Support vector machine regression (SVR/LS-SVM)—an alternative to neural networks (ANN) for analytical chemistry? Comparison of nonlinear methods on near infrared (NIR) spectroscopy data;Balabin;Analyst,2011

3. Artificial neural networks: fundamentals, computing, design, and application;Basheer;J. Microbiol. Methods,2000

4. D-Glucose-induced alterations in the electrical parameters of human erythrocyte cell membrane;Basio;Bioelectrochemistry,2010

5. Estimating electrical properties and the thickness of skin with electrical impedance spectroscopy: mathematical analysis and measurements;Birgersson;J. Electr. Bioimpedance,2012

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