Estimation of Interstitial Glucose from Physical Activity Measures Using Grammatical Evolution
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{cervigon:2023:GECCOcomp,
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author = "Carlos Cervigon and J. Ignacio Hidalgo",
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title = "Estimation of Interstitial Glucose from Physical
Activity Measures Using Grammatical Evolution",
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booktitle = "Proceedings of the 2023 Genetic and Evolutionary
Computation Conference",
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year = "2023",
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editor = "Justyna Petke and Aniko Ekart",
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pages = "57--58",
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address = "Lisbon, Portugal",
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series = "GECCO '23",
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month = "15-19 " # jul,
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organisation = "SIGEVO",
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publisher = "Association for Computing Machinery",
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publisher_address = "New York, NY, USA",
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keywords = "genetic algorithms, genetic programming, grammatical
evolution, blood glucose estimation, symbolic
regression",
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isbn13 = "9798400701191",
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DOI = "doi:10.1145/3583133.3596432",
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size = "2 pages",
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abstract = "People with diabetes need to have their glucose levels
under control, and it is essential for them to be able
to know or estimate their glucose levels at any time.
Continuous glucose monitors are commonly used, which
measure interstitial glucose, an approximation of blood
glucose, by means of a small catheter. Although most
devices are not very intrusive, they do present some
discomfort, and it would be preferable if these glucose
levels could be estimated non-invasively, for example,
through other physiological measurements collected in a
simple way. This abstract describes our research on the
performance of different grammatical evolution
techniques to obtain accurate estimations of actual
subcutaneous glucose values from non-invasive
physiological measures, steps, calories and heart rates
obtained with commercial smartwatches.",
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notes = "GECCO-2023 A Recombination of the 32nd International
Conference on Genetic Algorithms (ICGA) and the 28th
Annual Genetic Programming Conference (GP)",
- }
Genetic Programming entries for
Carlos Cervigon Ruckauer
Jose Ignacio Hidalgo Perez
Citations