Sep 12, 2018 · In this chapter we discuss a set of techniques based on GE to obtain mathematical models of the evolution of blood glucose along the time. These ...
This technique seeks to integrate the good results in the last years of Grammatical Evolution for blood glucose prediction, [6] [7] and the advantages of a ...
In this chapter we discuss a set of techniques based on GE to obtain mathematical models of the evolution of blood glucose along the time. These models help ...
Identification of Models for Glucose Blood Values in Diabetics by Grammatical Evolution. Created by W.Langdon from gp-bibliography.bib Revision:1.6946.
Identification of Models for Glucose Blood Values in Diabetics by Grammatical Evolution ... Authors: J. Ignacio Hidalgo; J. Manuel Colmenar; J. Manuel Velasco ...
Bibliographic details on Identification of Models for Glucose Blood Values in Diabetics by Grammatical Evolution.
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In this chapter we discuss a set of techniques based on GE to obtain mathematical models of the evolution of blood glucose along the time. These models help ...
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In this paper, we fill in this gap, by analyzing the performance of SGE when generating predictive models for the glucose levels of diabetic patients.
Learning Difference Equations With Structured Grammatical Evolution ...
pubmed.ncbi.nlm.nih.gov › ...
Combined with a previous clustering stage, our approach provides finite difference equations to predict postprandial glucose levels up to two hours after meals.
Jun 1, 2024 · This paper describes our research on predicting hypoglycemia events at 30, 60, 90, and 120 minutes using machine learning methods.