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Peter Drotar
Peter Drotar
Department of Computers and Informatics, Technical University of Kosice
Adresă de e-mail confirmată pe tuke.sk
Titlu
Citat de
Citat de
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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
3872016
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
2002014
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
1862014
Bankruptcy prediction for small-and medium-sized companies using severely imbalanced datasets
M Zoričák, P Gnip, P Drotár, V Gazda
Economic Modelling, 2019
1192019
Ensemble feature selection using election methods and ranker clustering
P Drotár, M Gazda, L Vokorokos
Information Sciences 480, 365-380, 2019
1072019
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
1072015
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
962021
Dysgraphia detection through machine learning
P Drotár, M Dobeš
Scientific reports 10 (1), 1-11, 2020
872020
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
842013
Self-supervised deep convolutional neural network for chest X-ray classification
M Gazda, J Gazda, J Plavka, P Drotar
IEEE Access, 2021
792021
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
742021
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
732013
On some aspects of minimum redundancy maximum relevance feature selection
P Bugata, P Drotar
Science China Information Sciences 63 (1), 1-15, 2020
682020
Selective oversampling approach for strongly imbalanced data
P Gnip, L Vokorokos, P Drotár
PeerJ Computer Science 7, e604, 2021
652021
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
592022
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
582015
Machine Learning Approach to Dysphonia Detection
Z Dankovičová, D Sovák, P Drotár, L Vokorokos
Applied Sciences 8 (10), 1927, 2018
552018
Weighted nearest neighbors feature selection
P Bugata, P Drotár
Knowledge-Based Systems 163, 749-761, 2019
362019
Deep convolutional neural network for detection of pathological speech
L Vavrek, M Hires, D Kumar, P Drotár
2021 IEEE 19th World Symposium on Applied Machine Intelligence and …, 2021
312021
Comparative study of machine learning techniques for supervised classification of biomedical data
P Drotár, Z Smékal
Acta Electrotechnica et Informatica 14 (3), 5-10, 2014
252014
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