Algebra of Pattern Matching Problems. - Václav Snásel; Tomas Koutny (Stringology, 1997)

Gradient Method with Topology Discovery for Load-Balancing in Active Networks. - Tomas Koutny; Jirí Safarík (ECBS, 2004)

Maintaining Communication Channels for Migrating Processes in the Environment of Active Networks. - Tomas Koutny; Jirí Safarík (Parallel and Distributed Computing and Networks, 2005)

Prediction of Interstitial Glucose Level. - Tomas Koutny (IEEE Trans. Inf. Technol. Biomed., 2012)

Glucose predictability, blood capillary permeability, and glucose utilization rate in subcutaneous, skeletal muscle, and visceral fat tissues. - Tomas Koutny (Comput. Biol. Medicine, 2013)

Experience with Lamport Clock Ordered Events with Intel Threading Building Blocks in a Glucose-Level Prediction Software. - Tomas Koutny (IWBBIO, 2014)

Blood glucose level reconstruction as a function of transcapillary glucose transport. - Tomas Koutny (Comput. Biol. Medicine, 2014)

On-line Blood Glucose Level Calculation. - Tomas Koutny; Michal Krcma; Josef Kohout; Petr Jezek; Jana Varnusková; Petr Vcelak; Jan Strnadek (EUSPN/ICTH, 2016)

Introducing the effect of aging into the Honey Bee Mating Optimization to determine parameters for blood glucose level calculation. - Jan Strnadek; Tomas Koutny; Josef Kohout (HSI, 2016)

Using meta-differential evolution to enhance a calculation of a continuous blood glucose level. - Tomas Koutny (Comput. Methods Programs Biomed., 2016)

Modelling of Glucose Dynamics for Diabetes. - Tomas Koutny (IWBBIO (1), 2017)

An Evolutionary Approach for Estimating the Blood Glucose by Exploiting Interstitial Glucose Measurements. - Ivanoe De Falco; Antonio Della Cioppa; Tomas Koutny; Michal Krcma; Umberto Scafuri; Ernesto Tarantino (HEALTHINF, 2018)

Parallel software architecture for the next generation of glucose monitoring. - Tomas Koutny; Martin Ubl (EUSPN/ICTH, 2018)

An evolutionary methodology for estimating blood glucose levels from interstitial glucose measurements and their derivatives. - Ivanoe De Falco; Umberto Scafuri; Ernesto Tarantino; Antonio Della Cioppa; A. Giugliano; Tomas Koutny; Michal Krcma (ISCC, 2018)

Genetic Programming-based induction of a glucose-dynamics model for telemedicine. - Ivanoe De Falco; Antonio Della Cioppa; Tomas Koutny; Michal Krcma; Umberto Scafuri; Ernesto Tarantino (J. Netw. Comput. Appl., 2018)

De-randomized Meta-Differential Evolution for Calculating and Predicting Glucose Levels. - Tomas Koutny; Antonio Della Cioppa; Ivanoe De Falco; Ernesto Tarantino; Umberto Scafuri; Michal Krcma (CBMS, 2019)

SmartCGMS as an Environment for an Insulin-Pump Development with FDA-Accepted In-Silico Pre-Clinical Trials. - Martin Ubl; Tomas Koutny (EUSPN/ICTH, 2019)

Comparing the PaGMO Framework to a De-randomized Meta-Differential Evolution on Calculation and Prediction of Glucose Levels. - Tomas Koutny; Martin Ubl; Ivan De Falco; Ernesto Tarantino; Umberto Scafuri; Antonio Della Cioppa; Michal Krcma (ISCC, 2019)

A genetic programming-based regression for extrapolating a blood glucose-dynamics model from interstitial glucose measurements and their first derivatives. - Ivanoe De Falco; Antonio Della Cioppa; A. Giugliano; Angelo Marcelli; Tomas Koutny; Michal Krcma; Umberto Scafuri; Ernesto Tarantino (Appl. Soft Comput., 2019)

Neural Multi-class Classification Approach to Blood Glucose Level Forecasting with Prediction Uncertainty Visualisation. - Michael Mayo; Tomas Koutny (KDH@ECAI, 2020)

SmartCGMS as a Testbed for a Blood-Glucose Level Prediction and/or Control Challenge with (an FDA-Accepted) Diabetic Patient Simulation. - Tomas Koutny; Martin Ubl (EUSPN/ICTH, 2020)

A Grammatical Evolution Approach for Estimating Blood Glucose Levels. - Ivanoe De Falco; Umberto Scafuri; Ernesto Tarantino; Antonio Della Cioppa; Tomas Koutny; Michal Krcma (GLOBECOM (Workshops), 2020)

Grammatical Evolution-Based Approach for Extracting Interpretable Glucose-Dynamics Models. - Ivanoe De Falco; Antonio Della Cioppa; Tomas Koutny; Umberto Scafuri; Ernesto Tarantino; Martin Ubl (ISCC, 2021)

A Novel Approach to Multi-Compartmental Model Implementation to Achieve Metabolic Model Identifiability on Patient's CGM Data. - Martin Ubl; Tomas Koutny (EUSPN/ICTH, 2022)

An Evolution-based Machine Learning Approach for Inducing Glucose Prediction Models. - Ivanoe De Falco; Antonio Della Cioppa; Tomas Koutny; Umberto Scafuri; Ernesto Tarantino; Martin Ubl (ISCC, 2022)

Predicting glucose level with an adapted branch predictor. - Tomas Koutny; Michael Mayo (Comput. Biol. Medicine, 2022)

Distributed Assessment of Virtual Insulin-Pump Settings Using SmartCGMS and DMMS.R for Diabetes Treatment. - Martin Ubl; Tomas Koutny; Antonio Della Cioppa; Ivanoe De Falco; Ernesto Tarantino; Umberto Scafuri (Sensors, 2022)

Reducing high-risk glucose forecasting errors by evolving interpretable models for Type 1 diabetes. - Antonio Della Cioppa; Ivan De Falco; Tomas Koutny; Umberto Scafuri; Martin Ubl; Ernesto Tarantino (Appl. Soft Comput., 2023)

A Federated Learning-Inspired Evolutionary Algorithm: Application to Glucose Prediction. - Ivanoe De Falco; Antonio Della Cioppa; Tomas Koutny; Martin Ubl; Michal Krcma; Umberto Scafuri; Ernesto Tarantino (Sensors, 2023)

Model-Free-Communication Federated Learning: Framework and application to Precision Medicine. - Ivanoe De Falco; Antonio Della Cioppa; Tomas Koutny; Umberto Scafuri; Ernesto Tarantino (Biomed. Signal Process. Control., 2024)

Online Simulation of a Diabetic-Patient Metabolism and a Realistic Meal Composition. - Tomas Koutny; Martin Ubl (CBMS, 2025)