Article

Glucose level prediction using artificial neural networks

Authors:

Eugen Iancu,

Ionela Iancu,

Dan Istrate,

Maria MotaAuthors Info & Claims

SMO'09: Proceedings of the 9th WSEAS international conference on Simulation, modelling and optimization

Pages 407 - 412

Published: 03 September 2009 Publication History

Abstract

The advanced treatment of the type I diabetes mellitus through closed-loop systems, such as artificial pancreas is one of today's greatest challenges. In this work the authors have tried to develop a predictive method which can be incorporated in an optimal system for blood glucose-insulin regulation. Using the neural network approach it is possible to compose a prediction model, very useful to control an insulin pump. Also, the artificial neural networks can be used to test and validate the medical decisions. The results of this study can be applied also, to other physiological systems, as it offers important data for the medical practice and it contributes to introduce the computer assisted diagnosis like a current medical method.

References

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Scott M. Pappada, Brent D. Cameron, Paul M. Rosnan, Development of a Neural Network for Prediction of Glucose Concentration in Type 1 Diabetes Patients, Journal of Diabetes Science and Technology, Volume 2, Issue 5, September 2008, pp. 792-793.

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Glucose level prediction using artificial neural networks
1. Applied computing
  1. Life and medical sciences
  2. Operations research
2. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
  2. Modeling and simulation
    1. Model development and analysis

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Published In

SMO'09: Proceedings of the 9th WSEAS international conference on Simulation, modelling and optimization

September 2009

477 pages

ISBN:9789604741137

Editors:
Rudas Imre
Budapest Tech, Hungary
,
Metin Demiralp
Istanbul Technical University, Turkey
,
Nikos Mastorakis
Technical University of Sofia, Bulgaria

Publisher

World Scientific and Engineering Academy and Society (WSEAS)

Stevens Point, Wisconsin, United States

Publication History

Published: 03 September 2009

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A method to early detect blood glucose variations using continuous glucose monitoring system

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A method to early detect blood glucose variations using continuous glucose monitoring system

On-line Blood Glucose Level Calculation

Spectral analysis of the blood glucose time series for automated diagnosis

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