Characterization of the temporal pattern of cerebral blood flow oscillations. - Balázs Benyó; Gábor Lenzser; Béla Paláncz (IJCNN, 2004)

Robust Blood-Glucose Control using Mathematica. - Levente Kovács; Béla Paláncz; Balázs Benyó; László Török; Zoltán Benyó (EMBC, 2006)

Classification of Time Series Using Singular Values and Wavelet Subband Analysis with ANN and SVM Classifiers. - Balázs Benyó; Péter Somogyi; Béla Paláncz (J. Adv. Comput. Intell. Intell. Informatics, 2006)

Glucose-Insulin Control of Type1 Diabetic Patients in H2/Hinfinity Space Via Computer Algebra. - Levente Kovács; Béla Paláncz (AB, 2007)

Solving Robust Glucose-Insulin Control by Dixon Resultant Computations. - Laura Kovács; Béla Paláncz; Levente Kovács (SYNASC, 2012)

Pareto optimality solution of the multi-objective photogrammetric resection-intersection problem. - Béla Paláncz; Joseph L. Awange (Earth Sci. Informatics, 2013)

Application of Dixon resultant to satellite trajectory control by pole placement. - Béla Paláncz (J. Symb. Comput., 2013)

Maximizing Likelihood Function for Parameter Estimation in Point Clouds via Groebner Basis. - Joseph L. Awange; Béla Paláncz; Robert H. Lewis (ICMS, 2014)

Groebner Basis in Geodesy and Geoinformatics. - Joseph L. Awange; Béla Paláncz; Robert H. Lewis (ICMS, 2014)

Application of Dixon resultant to maximization of the likelihood function of Gaussian mixture distribution. - Robert H. Lewis; Béla Paláncz; Joseph L. Awange (ACM Commun. Comput. Algebra, 2015)

Specific validation analysis of stochastic ICING model based estimation of insulin sensitivity profile using clinical data. - Balázs Benyó; Kent W. Stewart; Jozsef Homlok; Christopher G. Pretty; J. Geoffrey Chase; Béla Paláncz (SMC, 2016)

Fitting a Sphere via Gröbner Basis. - Robert H. Lewis; Béla Paláncz; Joseph L. Awange (ICMS, 2018)

Solving geoinformatics parametric polynomial systems using the improved Dixon resultant. - Robert H. Lewis; Béla Paláncz; Joseph L. Awange (Earth Sci. Informatics, 2019)

Classification-based deep neural network vs mixture density network models for insulin sensitivity prediction problem. - Balázs Benyó; Béla Paláncz; Ákos Szlávecz; Bálint Szabó; Katalin Kovács; J. Geoffrey Chase (Comput. Methods Programs Biomed., 2023)

Comparison of three artificial intelligence methods for predicting 90% quantile interval of future insulin sensitivity of intensive care patients. - Bálint Szabó; Ákos Szlávecz; Béla Paláncz; Omer S. Alkhafaf; Ameer B. Alsultani; Katalin Kovács; J. Geoffrey Chase; Balázs Benyó (IFAC J. Syst. Control., 2024)