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Modelling of Glucose Dynamics for Diabetes

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Bioinformatics and Biomedical Engineering (IWBBIO 2017)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 10208))

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Abstract

Diabetes is a heterogeneous group of diseases associated with elevated blood glucose level. Elevated glucose level continuously damages multiple organs, eventually leading to death. Diabetes is one of top 10 leading causes of death. Diabetes does not hurt nor manifests outwardly, until it is too late and the disease has developed. For example, type-1 diabetic patient depends on insulin. The patient takes insulin based on self-monitoring of blood glucose level. Motivated patient takes approximately 3-4 blood samples a day. This cannot capture all important events, e.g., nocturnal hypoglycemia with the risk of death. Therefore, the patient wears a system that continuously measures glucose level in the subcutaneous tissue. Nevertheless, these two glucose levels are not linearly proportional. They can differ considerably. Therefore, a model of glucose dynamics is needed to describe the non-linearity between these two levels. The model is important to estimate blood glucose level from the subcutaneous tissue glucose level and for a development of artificial pancreas. Number of models were developed. In this paper, we present the background, selected models of glucose dynamics, lessons learned and propose what minimal data researchers should share to stimulate further research on this topic.

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Acknowledgement

This publication was supported by the project LO1506 of the Czech Ministry of Education, Youth and Sports.

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Authors and Affiliations

  1. NTIS - New Technologies for the Information Society, University of West Bohemia, Univerzitni 8, 306 14, Plzen, Czech Republic

    Tomas Koutny

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  1. Tomas Koutny
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Correspondence to Tomas Koutny .

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Editors and Affiliations

  1. Universidad de Granada, Granada, Spain

    Ignacio Rojas

  2. Universidad de Granada, Granada, Spain

    Francisco Ortuño

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Koutny, T. (2017). Modelling of Glucose Dynamics for Diabetes. In: Rojas, I., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2017. Lecture Notes in Computer Science(), vol 10208. Springer, Cham. https://doi.org/10.1007/978-3-319-56148-6_27

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  • DOI: https://doi.org/10.1007/978-3-319-56148-6_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-56147-9

  • Online ISBN: 978-3-319-56148-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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