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Odpovídající záznamy:
Datum vydáníNázevAutor
2019SmartCGMS as an Environment for an Insulin-Pump Development with FDA-Accepted In-Silico Pre-Clinical TrialsÚbl, Martin; Koutný, Tomáš
2019Comparing the PaGMO Framework to a De-randomized Meta-Differential Evolution on Calculation and Prediction of Glucose LevelsKoutný, Tomáš; Úbl, Martin; Della Cioppa, Antonio; De Falco, Ivanoe; Tarantino, Ernesto; Umberto, Scafuri; Krčma, Michal
2018Parallel software architecture for the next generation of glucose monitoringKoutný, Tomáš; Úbl, Martin
2020SmartCGMS as a Testbed for a Blood-Glucose Level Prediction and/or Control Challenge with (an FDA-Accepted) Diabetic Patient SimulationKoutný, Tomáš; Úbl, Martin
2022Distributed Assessment of Virtual Insulin-Pump Settings Using SmartCGMS and DMMS.R for Diabetes TreatmentÚbl, Martin; Koutný, Tomáš; Della Cioppa, Antonio; De Falco, Ivanoe; Tarantino, Ernesto; Scafuri, Umberto
2021Grammatical Evolution-Based Approach for Extracting Interpretable Glucose-Dynamics ModelsDe Falco, Ivanoe; Della Cioppa, Antonio; Koutný, Tomáš; Scafuri, Umberto; Tarantino, Ernesto; Úbl, Martin
2022An Evolution-based Machine Learning Approach for Inducing Glucose Prediction ModelsDe Falco, Ivanoe; Della Cioppa, Antonio; Koutný, Tomáš; Scafuri, Umberto; Tarantino, Ernesto; Úbl, Martin
2023A Federated Learning-Inspired Evolutionary Algorithm: Application to Glucose PredictionDe Falco, Ivanoe; Della Cioppa, Antonio; Koutný, Tomáš; Úbl, Martin; Krčma, Michal; Scafuri, Umberto; Tarantino, Ernesto
2023Reducing high-risk glucose forecasting errors by evolving interpretable models for Type 1 diabetesDella Cioppa, Antonio; De Falco, Ivanoe; Koutný, Tomáš; Scafuri, Umberto; Úbl, Martin; Tarantino, Ernesto