| 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 | 362 | 2016 |
| 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 | 188 | 2014 |
| 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 | 177 | 2014 |
| Bankruptcy prediction for small-and medium-sized companies using severely imbalanced datasets M Zoričák, P Gnip, P Drotár, V Gazda Economic Modelling, 2019 | 110 | 2019 |
| Ensemble feature selection using election methods and ranker clustering P Drotár, M Gazda, L Vokorokos Information Sciences 480, 365-380, 2019 | 103 | 2019 |
| 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 | 102 | 2015 |
| 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 | 81 | 2021 |
| 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 | 80 | 2013 |
| Dysgraphia detection through machine learning P Drotár, M Dobeš Scientific reports 10 (1), 1-11, 2020 | 78 | 2020 |
| Self-supervised deep convolutional neural network for chest X-ray classification M Gazda, J Gazda, J Plavka, P Drotar IEEE Access, 2021 | 71 | 2021 |
| 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 | 71 | 2013 |
| 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 | 65 | 2021 |
| Selective oversampling approach for strongly imbalanced data P Gnip, L Vokorokos, P Drotár PeerJ Computer Science 7, e604, 2021 | 63 | 2021 |
| On some aspects of minimum redundancy maximum relevance feature selection P Bugata, P Drotar Science China Information Sciences 63 (1), 1-15, 2020 | 61 | 2020 |
| Machine Learning Approach to Dysphonia Detection Z Dankovičová, D Sovák, P Drotár, L Vokorokos Applied Sciences 8 (10), 1927, 2018 | 52 | 2018 |
| 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 | 52 | 2015 |
| 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 | 42 | 2022 |
| Weighted nearest neighbors feature selection P Bugata, P Drotár Knowledge-Based Systems 163, 749-761, 2019 | 36 | 2019 |
| 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 | 25 | 2021 |
| 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 | 25 | 2010 |
Jiri MekyskaBrno University of TechnologyVerified email at vut.cz
