Attentive Adversarial Network for Large-Scale Sleep Staging S Nasiri, GD Clifford Journal of Machine Learning Research (JMLR) - Machine Learning for Healthcare, 2020 | 30 | 2020 |
Generalizable Seizure Detection Model using Generating Transferable Adversarial Features S Nasiri, GD Clifford IEEE Signal Processing Letters, 2021 | 17 | 2021 |
Subject selection on a Riemannian manifold for unsupervised cross-subject seizure detection SNG Bolagh, G Clifford 31st Conference on Neural Information Processing Systems (NeurIPS), Long …, 2017 | 17 | 2017 |
A Deep Learning-Based Method for Automatic Detection of Epileptic Seizure in a Dataset With Both Generalized and Focal Seizure Types A Einizade, M Mozafari, SH Sardouie, S Nasiri, G Clifford | 15 | 2020 |
Development of expert-level classification of seizures and rhythmic and periodic patterns during eeg interpretation J Jing, W Ge, S Hong, MB Fernandes, Z Lin, C Yang, S An, AF Struck, ... Neurology 100 (17), e1750-e1762, 2023 | 14 | 2023 |
Explainable automated seizure detection using attentive deep multi-view networks A Einizade, S Nasiri, M Mozafari, SH Sardouie, GD Clifford Biomedical Signal Processing and Control 79, 104076, 2023 | 12 | 2023 |
Unsupervised cross-subject BCI learning and classification using Riemannian geometry SNG Bolagh, MB Shamsollahi, C Jutten, M Congedo 24th European Symposium on Artificial Neural Networks, Computational …, 2016 | 12 | 2016 |
Interrater reliability of expert electroencephalographers identifying seizures and rhythmic and periodic patterns in EEGs J Jing, W Ge, AF Struck, MB Fernandes, S Hong, S An, S Fatima, ... Neurology 100 (17), e1737-e1749, 2023 | 11 | 2023 |
ProductGraphSleepNet: Sleep staging using product spatio-temporal graph learning with attentive temporal aggregation A Einizade, S Nasiri, SH Sardouie, GD Clifford Neural Networks 164, 667-680, 2023 | 10 | 2023 |
Boosting Automated Sleep Staging Performance in Big Datasets using Population Sub-grouping S Nasiri, GD Clifford SLEEP, 2021 | 5 | 2021 |
Exploiting labels from multiple experts in automated sleep scoring S Nasiri, W Ganglberger, H Sun, RJ Thomas, MB Westover Sleep 46 (5), zsad034, 2023 | 3 | 2023 |
Neural circuits for dynamics-based segmentation of time series T Teşileanu, S Golkar, S Nasiri, AM Sengupta, DB Chklovskii Neural computation 34 (4), 891-938, 2022 | 3 | 2022 |
Predicting age, cognitive scores, and sleep stages from sleep EEG with a multi-task deep neural network using the Framingham Heart Study MBW W Ganglberger, N Adra, H Sun, S Nasiri, T Nassi, H-P Landolt, R Huber ... Sleep Medicine 100, S35, 2022 | 1 | 2022 |
From Sleep Patterns to Heart Rhythms: Predicting Atrial Fibrillation from Overnight Polysomnograms Z Koscova, AB Rad, S Nasiri, MA Reyna, R Sameni, LM Trotti, H Sun, ... medRxiv, 2024.06. 04.24308444, 2024 | | 2024 |
Interrater Reliability of Experts in Identifying Seizures and Highly Epileptiform Events in Electroencephalograms J Jing, W Ge, AF Struck, M Bento Fernandes, S Hong, S An, S Fatima, ... | | 2022 |
Importance Weighting with a Adversarial Network for Large-Scale Sleep Staging S Nasiri, GD Clifford 37th International Conference on Machine Learning (ICML), Vienna, Austria, 2020 | | 2020 |
System identification in the brain: inferring ARMA dynamics from sensory data T Tesileanu, S Nasiri, A Sengupta, D Chklovskii Bulletin of the American Physical Society, 2020 | | 2020 |