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2019 | OriginalPaper | Buchkapitel

A Logic-Based Learning Approach to Explore Diabetes Patient Behaviors

verfasst von : Josephine Lamp, Simone Silvetti, Marc Breton, Laura Nenzi, Lu Feng

Erschienen in: Computational Methods in Systems Biology

Verlag: Springer International Publishing

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Abstract

Type I Diabetes (T1D) is a chronic disease in which the body’s ability to synthesize insulin is destroyed. It can be difficult for patients to manage their T1D, as they must control a variety of behavioral factors that affect glycemic control outcomes. In this paper, we explore T1D patient behaviors using a Signal Temporal Logic (STL) based learning approach. STL formulas learned from real patient data characterize behavior patterns that may result in varying glycemic control. Such logical characterizations can provide feedback to clinicians and their patients about behavioral changes that patients may implement to improve T1D control. We present both individual- and population-level behavior patterns learned from a clinical dataset of 21 T1D patients.

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Titel: A Logic-Based Learning Approach to Explore Diabetes Patient Behaviors
verfasst von: Josephine Lamp
Simone Silvetti
Marc Breton
Laura Nenzi
Lu Feng
Verlag: Springer International Publishing
Buch: Computational Methods in Systems Biology
Print ISBN: 978-3-030-31303-6

Electronic ISBN: 978-3-030-31304-3

Copyright-Jahr: 2019
DOI: https://doi.org/10.1007/978-3-030-31304-3_10

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