Grammatical Evolution-Based Approach for Extracting Interpretable Glucose-Dynamics Models

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{conf/iscc/FalcoCKSTU21,

• author = "I. {De Falco} and Antonio Della Cioppa and Tomas Koutny and Umberto Scafuri and Ernesto Tarantino and Martin Ubl",
• title = "Grammatical Evolution-Based Approach for Extracting Interpretable Glucose-Dynamics Models",
• booktitle = "2021 IEEE Symposium on Computers and Communications (ISCC)",
• year = "2021",
• address = "Athens, Greece",
• month = "5-8 " # sep,
• publisher = "IEEE",
• keywords = "genetic algorithms, genetic programming, grammatical evolution",
• isbn13 = "978-1-6654-2744-9",
• bibdate = "2021-12-17",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/iscc/iscc2021.html#FalcoCKSTU21",
• DOI = "doi:10.1109/ISCC53001.2021.9631483",
• 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