| Machine learning framework for the detection of mental stress at multiple levels AR Subhani, W Mumtaz, MNBM Saad, N Kamel, AS Malik IEEE Access 5, 13545-13556, 2017 | 290 | 2017 |
| Classification of EEG signals based on pattern recognition approach HU Amin, W Mumtaz, AR Subhani, MNM Saad, AS Malik Frontiers in computational neuroscience 11, 103, 2017 | 217 | 2017 |
| Electroencephalogram (EEG)-based computer-aided technique to diagnose major depressive disorder (MDD) W Mumtaz, L Xia, SSA Ali, MAM Yasin, M Hussain, AS Malik Biomedical Signal Processing and Control 31, 108-115, 2017 | 207 | 2017 |
| A wavelet-based technique to predict treatment outcome for major depressive disorder W Mumtaz, L Xia, MA Mohd Yasin, SS Azhar Ali, AS Malik PloS one 12 (2), e0171409, 2017 | 190 | 2017 |
| A machine learning framework involving EEG-based functional connectivity to diagnose major depressive disorder (MDD) W Mumtaz, SSA Ali, MAM Yasin, AS Malik Medical & biological engineering & computing 56, 233-246, 2018 | 184 | 2018 |
| A deep learning framework for automatic diagnosis of unipolar depression W Mumtaz, A Qayyum International journal of medical informatics 132, 103983, 2019 | 152 | 2019 |
| Review of challenges associated with the EEG artifact removal methods W Mumtaz, S Rasheed, A Irfan Biomedical Signal Processing and Control 68, 102741, 2021 | 138 | 2021 |
| An EEG-based machine learning method to screen alcohol use disorder W Mumtaz, PL Vuong, L Xia, AS Malik, RBA Rashid Cognitive neurodynamics 11, 161-171, 2017 | 88 | 2017 |
| Review on EEG and ERP predictive biomarkers for major depressive disorder W Mumtaz, AS Malik, MAM Yasin, L Xia Biomedical Signal Processing and Control 22, 85-98, 2015 | 84 | 2015 |
| A review on EEG-based methods for screening and diagnosing alcohol use disorder W Mumtaz, PL Vuong, AS Malik, RBA Rashid Cognitive neurodynamics 12, 141-156, 2018 | 73 | 2018 |
| Automatic diagnosis of alcohol use disorder using EEG features W Mumtaz, PL Vuong, L Xia, AS Malik, RB Abd Rashid Knowledge-Based Systems 105, 48-59, 2016 | 65 | 2016 |
| An EEG-based functional connectivity measure for automatic detection of alcohol use disorder W Mumtaz, N Kamel, SSA Ali, AS Malik Artificial intelligence in medicine 84, 79-89, 2018 | 64 | 2018 |
| EEG in classroom: EMD features to detect situational interest of students during learning A Babiker, I Faye, W Mumtaz, AS Malik, H Sato Multimedia Tools and Applications 78 (12), 16261-16281, 2019 | 45 | 2019 |
| MDD patients and healthy controls EEG data (new) W Mumtaz figshare, Dataset, 2016 | 40 | 2016 |
| MRMR based feature selection for the classification of stress using EEG AR Subhani, W Mumtaz, N Kamil, NM Saad, N Nandagopal, AS Malik 2017 Eleventh International Conference on Sensing Technology (ICST), 1-4, 2017 | 34 | 2017 |
| Analysis of EEG signals regularity in adults during video game play in 2D and 3D HR Khairuddin, AS Malik, W Mumtaz, N Kamel, L Xia 2013 35th Annual International Conference of the IEEE Engineering in …, 2013 | 25 | 2013 |
| Detrended fluctuation analysis for major depressive disorder W Mumtaz, AS Malik, SSA Ali, MAM Yasin, H Amin 2015 37th Annual International Conference of the IEEE Engineering in …, 2015 | 22 | 2015 |
| Investigating neurofeedback protocols for stress mitigation: a comparative analysis of different stimulus contents Y Hafeez, SSA Ali, W Mumtaz, M Moinuddin, SH Adil, UM Al-Saggaf, ... IEEE access 7, 141021-141035, 2019 | 21 | 2019 |
| Automatic segmentation using a hybrid dense network integrated with an 3D-atrous spatial pyramid pooling module for computed tomography (CT) imaging A Qayyum, I Ahmad, W Mumtaz, MO Alassafi, R Alghamdi, M Mazher IEEE Access 8, 169794-169803, 2020 | 19 | 2020 |
| A comparative study of different EEG reference choices for diagnosing unipolar depression W Mumtaz, AS Malik Brain Topography 31 (5), 875-885, 2018 | 18 | 2018 |
Aamir Saeed MalikFaculty of IT, Brno University of TechnologyVahvistettu sähköpostiosoite verkkotunnuksessa fit.vut.cz