Artur Szymanski

Publication Activity (10 Years)

Years Active: 2006-2020
Publications (10 Years): 8

Top Topics

Deep Brain Stimulation

Rough Sets Theory

Building Intelligent

Top Venues

Brain Informatics and Health

Publications

Artur Chudzik, Artur Szymanski, Jerzy Pawel Nowacki, Andrzej W. Przybyszewski
Eye-Tracking and Machine Learning Significance in Parkinson's Disease Symptoms Prediction. ACIIDS (2) (2020)
Albert Sledzianowski, Artur Szymanski, Aldona Drabik, Stanislaw Szlufik, Dariusz M. Koziorowski, Andrzej W. Przybyszewski
Combining Results of Different Oculometric Tests Improved Prediction of Parkinson's Disease Development. ACIIDS (2) (2020)
Artur Chudzik, Artur Szymanski, Jerzy Pawel Nowacki, Andrzej W. Przybyszewski
DTI Helps to Predict Parkinson's Patient's Symptoms Using Data Mining Techniques. ACIIDS (2) (2019)
Albert Sledzianowski, Artur Szymanski, Aldona Drabik, Stanislaw Szlufik, Dariusz M. Koziorowski, Andrzej W. Przybyszewski
Measurements of Antisaccades Parameters Can Improve the Prediction of Parkinson's Disease Progression. ACIIDS (2) (2019)
Albert Sledzianowski, Artur Szymanski, Stanislaw Szlufik, Dariusz M. Koziorowski
Rough Set Data Mining Algorithms and Pursuit Eye Movement Measurements Help to Predict Symptom Development in Parkinson's Disease. ACIIDS (2) (2018)
Artur Szymanski, Stanislaw Szlufik, Dariusz M. Koziorowski, Andrzej W. Przybyszewski
Building Classifiers for Parkinson's Disease Using New Eye Tribe Tracking Method. ACIIDS (2) (2017)
Andrzej W. Przybyszewski, Mark A. Kon, Stanislaw Szlufik, Artur Szymanski, Piotr Habela, Dariusz M. Koziorowski
Multimodal Learning and Intelligent Prediction of Symptom Development in Individual Parkinson's Patients. Sensors 16 (9) (2016)
Artur Szymanski, Stanislaw Szlufik, Dariusz M. Koziorowski, Piotr Habela, Andrzej W. Przybyszewski
Building Intelligent Classifiers for Doctor-Independent Parkinson's Disease Treatments. ITIB (1) (2016)
Artur Szymanski, Stanislaw Szlufik, Justyna Dutkiewicz, Dariusz M. Koziorowski, Marek Cacko, Michal Nieniecki, Andrzej W. Przybyszewski
Data mining using SPECT can predict neurological symptom development in Parkinson's patients. CYBCONF (2015)
Anna Kubis, Artur Szymanski, Andrzej W. Przybyszewski
Fuzzy Rough Sets Theory Applied to Parameters of Eye Movements Can Help to Predict Effects of Different Treatments in Parkinson's Patients. PReMI (2015)
Artur Szymanski
Data mining and neural network simulations can help to improve Deep Brain Stimulation effects in Parkinson Disease. Comput. Sci. 16 (2) (2015)
Artur Szymanski, Andrzej W. Przybyszewski
Rough Set Rules Help to Optimize Parameters of Deep Brain Stimulation in Parkinson's Patients. Brain Informatics and Health (2014)
Shonda Gosselin, Artur Szymanski, Adam Pawel Wojda
Cyclic partitions of complete nonuniform hypergraphs and complete multipartite hypergraphs. Discret. Math. Theor. Comput. Sci. 15 (2) (2013)
Artur Szymanski, A. Pawel Wojda
Cyclic Partitions of Complete Uniform Hypergraphs. Electron. J. Comb. 17 (1) (2010)
Artur Szymanski, A. Pawel Wojda
-uniform self-complementary hypergraphs of given order. Discuss. Math. Graph Theory 29 (1) (2009)
Lech Adamus, Beata Orchel, Artur Szymanski, A. Pawel Wojda, Malgorzata Zwonek
A note on t-complementing permutations for graphs. Inf. Process. Lett. 110 (2) (2009)
Artur Szymanski, A. Pawel Wojda
Self-complementing permutations of k-uniform hypergraphs. Discret. Math. Theor. Comput. Sci. 11 (1) (2009)
Aneta Dudek, Artur Szymanski, Malgorzata Zwonek
stable graphs with minimum size. Discuss. Math. Graph Theory 28 (1) (2008)
Artur Szymanski, A. Pawel Wojda
Self-complementary hypergraphs and their self-complementing permutations. Electron. Notes Discret. Math. 24 (2006)