Grammatical Evolution-Based Approach for Extracting Interpretable Glucose-Dynamics Models
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{conf/iscc/FalcoCKSTU21,
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author = "I. {De Falco} and Antonio Della Cioppa and
Tomas Koutny and Umberto Scafuri and Ernesto Tarantino and
Martin Ubl",
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title = "Grammatical Evolution-Based Approach for Extracting
Interpretable Glucose-Dynamics Models",
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booktitle = "2021 IEEE Symposium on Computers and Communications
(ISCC)",
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year = "2021",
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address = "Athens, Greece",
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month = "5-8 " # sep,
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publisher = "IEEE",
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keywords = "genetic algorithms, genetic programming, grammatical
evolution",
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isbn13 = "978-1-6654-2744-9",
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bibdate = "2021-12-17",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/conf/iscc/iscc2021.html#FalcoCKSTU21",
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DOI = "doi:10.1109/ISCC53001.2021.9631483",
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abstract = "The quality of life of diabetic patients can be
enhanced by devising a personalized control algorithm,
integrated within an artificial pancreas, capable of
dosing the insulin. A key action in the building of
this artificial device is to conceive an efficient
algorithm for forecasting future glucose levels. Within
this paper, an evolutionary-based strategy, i.e., a
Grammatical Evolution algorithm, is devised to deduce a
personalized forecasting model to evaluate blood
glucose values in the future on the basis of the past
glucose measurements, and the knowledge of the basal
and infused insulin levels and of the food consumption.
The aim is to discover models that are not only
interpretable but also with low complexity to be used
within a control algorithm that is the main element of
the artificial pancreas. A real-world database composed
by Type 1 diabetic patients has been employed to
evaluate the proposed evolutionary automatic
procedure.",
- }
Genetic Programming entries for
Ivanoe De Falco
Antonio Della Cioppa
Tomas Koutny
Umberto Scafuri
Ernesto Tarantino
Martin Ubl
Citations