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Peter Drotar
Peter Drotar
Department of Computers and Informatics, Technical University of Kosice
Verified email at tuke.sk
Title
Cited by
Cited by
Year
Evaluation of handwriting kinematics and pressure for differential diagnosis of Parkinson's disease
P Drotár, J Mekyska, I Rektorová, L Masarová, Z Smékal, ...
Artificial intelligence in medicine 67, 39-46, 2016
3242016
Decision support framework for Parkinson's disease based on novel handwriting markers
P Drotar, J Mekyska, I Rektorova, L Masarova, Z Smekal, M Zanuy
IEEE Transactions on Neural and Rehabilitation Engineering, 2014
1692014
Analysis of in-air movement in handwriting: A novel marker for Parkinson's disease
P Drotár, J Mekyska, I Rektorová, L Masarová, Z Smékal, ...
Computer methods and programs in biomedicine 117 (3), 405-411, 2014
1602014
An experimental comparison of feature selection methods on two-class biomedical datasets
P Drotár, J Gazda, Z Smékal
Computers in biology and medicine 66, 1-10, 2015
982015
Bankruptcy prediction for small-and medium-sized companies using severely imbalanced datasets
M Zoričák, P Gnip, P Drotár, V Gazda
Economic Modelling, 2019
932019
Ensemble feature selection using election methods and ranker clustering
P Drotár, M Gazda, L Vokorokos
Information Sciences 480, 365-380, 2019
842019
A new modality for quantitative evaluation of Parkinson's disease: In-air movement
P Drotár, J Mekyska, I Rektorova, L Masarova, Z Smékal, ...
Bioinformatics and Bioengineering (BIBE), 2013 IEEE 13th International …, 2013
722013
Dysgraphia detection through machine learning
P Drotár, M Dobeš
Scientific reports 10 (1), 1-11, 2020
682020
Prediction potential of different handwriting tasks for diagnosis of Parkinson's
P Drotar, J Mekyska, Z Smekal, I Rektorova, L Masarova, ...
E-Health and Bioengineering Conference (EHB), 2013, 1-4, 2013
682013
Convolutional neural network ensemble for Parkinson's disease detection from voice recordings
M Hireš, M Gazda, P Drotár, ND Pah, MA Motin, DK Kumar
Computers in Biology and Medicine, 105021, 2021
592021
Multiple-Fine-Tuned Convolutional Neural Networks for Parkinson's Disease Diagnosis From Offline Handwriting
M Gazda, M Hireš, P Drotár
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021
552021
Self-supervised deep convolutional neural network for chest X-ray classification
M Gazda, J Gazda, J Plavka, P Drotar
IEEE Access, 2021
532021
On some aspects of minimum redundancy maximum relevance feature selection
P Bugata, P Drotar
Science China Information Sciences 63 (1), 1-15, 2020
502020
Selective oversampling approach for strongly imbalanced data
P Gnip, L Vokorokos, P Drotár
PeerJ Computer Science 7, e604, 2021
482021
Contribution of different handwriting modalities to differential diagnosis of Parkinson's Disease
P Drotar, J Mekyska, Z Smékal, I Rektorova, L Masarova, ...
Medical Measurements and Applications (MeMeA), 2015 IEEE International …, 2015
472015
Machine Learning Approach to Dysphonia Detection
Z Dankovičová, D Sovák, P Drotár, L Vokorokos
Applied Sciences 8 (10), 1927, 2018
432018
Weighted nearest neighbors feature selection
P Bugata, P Drotár
Knowledge-Based Systems 163, 749-761, 2019
342019
Computerized Analysis of Speech and Voice for Parkinson's Disease: A Systematic Review
QC Ngo, MA Motin, ND Pah, P Drotár, P Kempster, D Kumar
Computer Methods and Programs in Biomedicine, 107133, 2022
262022
Receiver technique for iterative estimation and cancellation of nonlinear distortion in MIMO SFBC-OFDM systems
P Drotár, J Gazda, P Galajda, D Kocur, P Pavelka
Consumer Electronics, IEEE Transactions on 56 (2), 471-475, 2010
232010
Receiver based compensation of nonlinear distortion in MIMO-OFDM
P Drotar, J Gazda, M Deumal, P Galajda, D Kocur
RF Front-ends for Software Defined and Cognitive Radio Solutions (IMWS …, 2010
232010
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