Andrzej W. Przybyszewski
Orcid: 0000-0002-0156-7856
According to our database1,
Andrzej W. Przybyszewski
authored at least 69 papers
between 1996 and 2024.
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Bibliography
2024
Machine Learning and Digital Biomarkers Can Detect Early Stages of Neurodegenerative Diseases.
Sensors, March, 2024
Recognizing Patterns of Parkinson's Disease Using Online Trail Making Test and Response Dynamics - Preliminary Study.
Proceedings of the Pattern Recognition - 27th International Conference, 2024
2023
Machine Learning and Eye Movements Give Insights into Neurodegenerative Disease Mechanisms.
Sensors, February, 2023
Universal Machine-Learning Processing Pattern for Computing in the Video-Oculography.
Proceedings of the Computational Science - ICCS 2023, 2023
Multi-granular Computing Can Predict Prodromal Alzheimer's Disease Indications in Normal Subjects.
Proceedings of the Computational Science - ICCS 2023, 2023
Proceedings of the Recent Challenges in Intelligent Information and Database Systems, 2023
Granular Computing to Forecast Alzheimer's Disease Distinctive Individual Development.
Proceedings of the Intelligent Information and Database Systems - 15th Asian Conference, 2023
Investigating the Impact of Parkinson's Disease on Brain Computations: An Online Study of Healthy Controls and PD Patients.
Proceedings of the Intelligent Information and Database Systems - 15th Asian Conference, 2023
2022
AI Classifications Applied to Neuropsychological Trials in Normal Individuals that Predict Progression to Cognitive Decline.
Proceedings of the Computational Science - ICCS 2022, 2022
Detecting True and Declarative Facial Emotions by Changes in Nonlinear Dynamics of Eye Movements.
Proceedings of the Intelligent Information and Database Systems - 14th Asian Conference, 2022
Rough Set Rules (RSR) Predominantly Based on Cognitive Tests Can Predict Alzheimer's Related Dementia.
Proceedings of the Intelligent Information and Database Systems - 14th Asian Conference, 2022
2021
Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 25th International Conference KES-2021, 2021
Proceedings of the Computational Collective Intelligence - 13th International Conference, 2021
Proceedings of the Computational Science - ICCS 2021, 2021
2020
Parkinson's disease development prediction by c-granule computing compared to different AI methods.
J. Inf. Telecommun., 2020
Comparison of Different Data Mining Methods to Determine Disease Progression in Dissimilar Groups of Parkinson's Patients.
Fundam. Informaticae, 2020
Combining Results of Different Oculometric Tests Improved Prediction of Parkinson's Disease Development.
Proceedings of the Intelligent Information and Database Systems - 12th Asian Conference, 2020
IGrC: Cognitive and Motor Changes During Symptoms Development in Parkinson's Disease Patients.
Proceedings of the Intelligent Information and Database Systems - 12th Asian Conference, 2020
Eye-Tracking and Machine Learning Significance in Parkinson's Disease Symptoms Prediction.
Proceedings of the Intelligent Information and Database Systems - 12th Asian Conference, 2020
2019
SI: SCA Measures - Fuzzy rough set features of cognitive computations in the visual system.
J. Intell. Fuzzy Syst., 2019
Proceedings of the Computational Collective Intelligence - 11th International Conference, 2019
Measurements of Antisaccades Parameters Can Improve the Prediction of Parkinson's Disease Progression.
Proceedings of the Intelligent Information and Database Systems - 11th Asian Conference, 2019
Granular Computing (GC) Demonstrates Interactions Between Depression and Symptoms Development in Parkinson's Disease Patients.
Proceedings of the Intelligent Information and Database Systems - 11th Asian Conference, 2019
Proceedings of the Intelligent Information and Database Systems - 11th Asian Conference, 2019
Multimodal Learning Determines Rules of Disease Development in Longitudinal Course with Parkinson's Patients.
Proceedings of the Intelligent Methods and Big Data in Industrial Applications., 2019
2018
Fuzzy RST and RST Rules Can Predict Effects of Different Therapies in Parkinson's Disease Patients.
Proceedings of the Foundations of Intelligent Systems - 24th International Symposium, 2018
Rules Determine Therapy-Dependent Relationship in Symptoms Development of Parkinson's Disease Patients.
Proceedings of the Intelligent Information and Database Systems - 10th Asian Conference, 2018
2017
Fundam. Informaticae, 2017
Rough Set Rules Determine Disease Progressions in Different Groups of Parkinson's Patients.
Proceedings of the Pattern Recognition and Machine Intelligence, 2017
Proceedings of the Intelligent Information and Database Systems - 9th Asian Conference, 2017
Rules Found by Multimodal Learning in One Group of Patients Help to Determine Optimal Treatment to Other Group of Parkinson's Patients.
Proceedings of the Intelligent Information and Database Systems - 9th Asian Conference, 2017
2016
Multimodal Learning and Intelligent Prediction of Symptom Development in Individual Parkinson's Patients.
Sensors, 2016
Building Intelligent Classifiers for Doctor-Independent Parkinson's Disease Treatments.
Proceedings of the Information Technologies in Medicine - 5th International Conference, 2016
2015
Fuzzy Rough Sets Theory Applied to Parameters of Eye Movements Can Help to Predict Effects of Different Treatments in Parkinson's Patients.
Proceedings of the Pattern Recognition and Machine Intelligence, 2015
Proceedings of the Foundations of Intelligent Systems - 22nd International Symposium, 2015
Data mining using SPECT can predict neurological symptom development in Parkinson's patients.
Proceedings of the 2nd IEEE International Conference on Cybernetics, 2015
Machine Learning on the Video Basis of Slow Pursuit Eye Movements Can Predict Symptom Development in Parkinson's Patients.
Proceedings of the Intelligent Information and Database Systems - 7th Asian Conference, 2015
Proceedings of the Intelligent Information and Database Systems - 7th Asian Conference, 2015
2014
Foundations of automatic system for intrasurgical localization of subthalamic nucleus in Parkinson patients.
Web Intell. Agent Syst., 2014
Data Mining and Machine Learning on the Basis from Reflexive Eye Movements Can Predict Symptom Development in Individual Parkinson's Patients.
Proceedings of the Nature-Inspired Computation and Machine Learning, 2014
Proceedings of the Foundations of Intelligent Systems - 21st International Symposium, 2014
Rough Set Rules Help to Optimize Parameters of Deep Brain Stimulation in Parkinson's Patients.
Proceedings of the Brain Informatics and Health - International Conference, 2014
Intraoperative Decision Making with Rough Set Rules for STN DBS in Parkinson Disease.
Proceedings of the Brain Informatics and Health - International Conference, 2014
Proceedings of the Intelligent Information and Database Systems - 6th Asian Conference, 2014
2013
DCworms - A tool for simulation of energy efficiency in distributed computing infrastructures.
Simul. Model. Pract. Theory, 2013
Discrimination of the Micro Electrode Recordings for STN Localization during DBS Surgery in Parkinson's Patients.
Proceedings of the Flexible Query Answering Systems - 10th International Conference, 2013
2012
Foundations of Recommender System for STN Localization during DBS Surgery in Parkinson's Patients.
Proceedings of the Foundations of Intelligent Systems - 20th International Symposium, 2012
A System for Analysis of Tremor in Patients with Parkinson's Disease Based on Motion Capture Technique.
Proceedings of the Computer Vision and Graphics - International Conference, 2012
2011
Proceedings of the Foundations of Intelligent Systems - 19th International Symposium, 2011
2010
Emd Approach to Multichannel EEG Data - the amplitude and Phase Components Clustering Analysis.
J. Circuits Syst. Comput., 2010
Cogn. Syst. Res., 2010
2009
Proceedings of the Seventh International Conference on Advances in Pattern Recognition, 2009
2008
Trans. Rough Sets, 2008
Proceedings of the Foundations of Intelligent Systems, 17th International Symposium, 2008
EMD Approach to Multichannel EEG Data - The Amplitude and Phase Synchrony Analysis Technique.
Proceedings of the Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues, 2008
Proceedings of the Artificial Neural Networks, 2008
Proceedings of the Visions of Computer Science, 2008
2007
Basic Difference Between Brain and Computer: Integration of Asynchronous Processes Implemented as Hardware Model of the Retina.
IEEE Trans. Neural Networks, 2007
Proceedings of the Rough Sets and Intelligent Systems Paradigms, International Conference, 2007
Proceedings of the Pattern Recognition and Machine Intelligence, 2007
Proceedings of the Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence, 2007
2005
Proceedings of the Intelligent Information Processing and Web Mining, 2005
Statistical Likelihood Representations of Prior Knowledge in Machine Learning.
Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, 2005
2000
Brain Differently Changes its Algorithms in Parallel Processing of Visual Information.
Proceedings of the Intelligent Information Systems, 2000
1998
1997
1996
On the complex dynamics of intracellular ganglion cell light responses in the cat retina.
Biol. Cybern., 1996