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Ahmed El-Gazzar
Ahmed El-Gazzar
PhD Candidate at AMC, Department of Psychaitry
Verified email at amsterdamumc.nl
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Cited by
Cited by
Year
Classifying autism spectrum disorder using the temporal statistics of resting-state functional MRI data with 3D convolutional neural networks
RM Thomas, S Gallo, L Cerliani, P Zhutovsky, A El-Gazzar, G Van Wingen
Frontiers in psychiatry 11, 440, 2020
612020
A hybrid 3DCNN and 3DC-LSTM based model for 4D spatio-temporal fMRI data: an ABIDE autism classification study
A El-Gazzar, M Quaak, L Cerliani, P Bloem, G van Wingen, ...
OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical …, 2019
352019
Simple 1-D convolutional networks for resting-state fMRI based classification in autism
A El Gazzar, L Cerliani, G van Wingen, RM Thomas
2019 International Joint Conference on Neural Networks (IJCNN), 1-6, 2019
292019
Fusing structural and functional MRIs using graph convolutional networks for autism classification
D Arya, R Olij, DK Gupta, A El Gazzar, G Wingen, M Worring, RM Thomas
Medical imaging with deep learning, 44-61, 2020
182020
Non-Contact manipulation of microbeads via pushing and pulling using magnetically controlled clusters of paramagnetic microparticles
AG El-Gazzar, LE Al-Khouly, A Klingner, S Misra, ISM Khalil
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015
182015
Dynamic adaptive spatio-temporal graph convolution for fMRI modelling
A El-Gazzar, RM Thomas, G van Wingen
Machine Learning in Clinical Neuroimaging: 4th International Workshop, MLCN …, 2021
42021
Thalamic hyperconnectivity as neurophysiological signature of major depressive disorder in two multicenter studies
S Gallo, A ElGazzar, P Zhutovsky, RM Thomas, N Javaheripour, L Meng, ...
PsyArXiv, 2021
22021
Improving the Diagnosis of Psychiatric Disorders with Self-Supervised Graph State Space Models
AE Gazzar, RM Thomas, G Van Wingen
arXiv preprint arXiv:2206.03331, 2022
12022
Benchmarking Graph Neural Networks for FMRI analysis
A ElGazzar, R Thomas, G Van Wingen
arXiv preprint arXiv:2211.08927, 2022
2022
fMRI-S4: learning short-and long-range dynamic fMRI dependencies using 1D Convolutions and State Space Models
A El-Gazzar, RM Thomas, G Van Wingen
Machine Learning in Clinical Neuroimaging: 5th International Workshop, MLCN …, 2022
2022
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