Prediction of treatment response in major depressive disorder using a hybrid of convolutional recurrent deep neural networks and effective connectivity based on EEG signal SM Mirjebreili, R Shalbaf, A Shalbaf Physical and Engineering Sciences in Medicine, 1-10, 2024 | 1 | 2024 |
Early electrophysiological aberrations in the Hippocampus of the TgF344-AD rat model as a potential biomarker for Alzheimer’s disease prognosis F Moradi, M van den Berg, M Mirjebreili, L Kosten, M Verhoye, M Amiri, ... bioRxiv, 2022.07. 01.498373, 2022 | 1 | 2022 |
Early classification of Alzheimer's disease phenotype based on hippocampal electrophysiology in the TgF344-AD rat model F Moradi, M van den Berg, M Mirjebreili, L Kosten, M Verhoye, M Amiri, ... Iscience 26 (8), 2023 | | 2023 |
Brain Activity Flow and Machine Learning for Predicting Drug Response in Patients SM Mirjebreili, R Shalbaf, A Shalbaf IEEE Transactions on Cognitive and Developmental Systems 15 (3), 1279-1288, 2023 | | 2023 |
Multi-Task Transformer for Stock Market Trend Prediction SM Mirjebreili, A Solouki, H Soltanalizadeh, M Sabokrou 2022 12th International Conference on Computer and Knowledge Engineering …, 2022 | | 2022 |
Brain Activity Flow and Machine Learning for Predicting Drug Response in Patients with Major Depressive Disorder SM Mirjebreili, R Shalbaf, A Shalbaf Basic and Clinical Neuroscience, 0-0, 0 | | |