| The simple chaotic model of passive dynamic walking S Montazeri Moghadam, M Sadeghi Talarposhti, A Niaty, F Towhidkhah, ... Nonlinear Dynamics 93, 1183-1199, 2018 | 37 | 2018 |
| Nonlinear analysis and synthesis of video images using deep dynamic bottleneck neural networks for face recognition SM Moghadam, SA Seyyedsalehi Neural Networks 105, 304-315, 2018 | 21 | 2018 |
| Building an open source classifier for the neonatal EEG background: a systematic feature-based approach from expert scoring to clinical visualization SM Moghadam, E Pinchefsky, I Tse, V Marchi, J Kohonen, M Kauppila, ... Frontiers in human neuroscience 15, 675154, 2021 | 18 | 2021 |
| Real-time prediction of tumor motion using a dynamic neural network M Mafi, S Montazeri Moghadam Medical & Biological Engineering & Computing, 1-11, 2020 | 14 | 2020 |
| An automated bedside measure for monitoring neonatal cortical activity: a supervised deep learning-based electroencephalogram classifier with external cohort validation SM Moghadam, M Airaksinen, P Nevalainen, V Marchi, ... The Lancet Digital Health 4 (12), e884-e892, 2022 | 12 | 2022 |
| Sleep State Trend (SST), a bedside measure of neonatal sleep state fluctuations based on single EEG channels SM Moghadam, P Nevalainen, NJ Stevenson, S Vanhatalo Clinical Neurophysiology 143, 75-83, 2022 | 9 | 2022 |
| Ensemble learning using individual neonatal data for seizure detection A Borovac, S Gudmundsson, G Thorvardsson, SM Moghadam, ... IEEE Journal of Translational Engineering in Health and Medicine 10, 1-11, 2022 | 9 | 2022 |
| Nonlinear analysis of video images using deep recurrent auto-associative neural networks for facial understanding SM Moghadam, SA Seyyedsalehi 2017 3rd International Conference on Pattern Recognition and Image Analysis …, 2017 | 4 | 2017 |
| Impact of steganography on jpeg file size M Rezaei, SM Moghadam 2019 27th Iranian Conference on Electrical Engineering (ICEE), 1869-1873, 2019 | 3 | 2019 |
| Nonlinear Synthesis of Expression Variation Dynamics on Video Using Deep Dynamic Bottleneck Neural Networks SM Moghadam, SA Seyyedsalehi, N Amini 2017 24th National and 2nd International Iranian Conference on Biomedical …, 2018 | 2 | 2018 |
| Improving stabilization of passive walking using chaos SM Moghadam, A Niaty, F Towhidkhah 2016 23rd Iranian Conference on Biomedical Engineering and 2016 1st …, 2016 | 2 | 2016 |
| Scramble and Transform: An Image Data Hiding Technique M Rezaei, SM Moghaddam 2019 27th Iranian Conference on Electrical Engineering (ICEE), 1874-1878, 2019 | 1 | 2019 |
| Clinical outcome prediction with an automated EEG trend, Brain State of the Newborn, after perinatal asphyxia S Montazeri, P Nevalainen, M Metsäranta, NJ Stevenson, S Vanhatalo Clinical Neurophysiology 162, 68-76, 2024 | | 2024 |
| Advancing Automated EEG Analysis for Neonatal Intensive Care: From Engineering to Bedside Solutions S Montazeri Moghadam Helsingin yliopisto, 2024 | | 2024 |
| Neurodevelopmental Outcome Prediction with an Automated Assessment of EEG Background at 24 Hours in Neonatal Encephalopathy Treated with Therapeutic Hypothermia M Lagacé, S Montazeri Moghadam, D Kamino, E Mamak, LG Ly, C Hahn, ... Available at SSRN 4746949, 2020 | | 2020 |
| Corrigendum: Building an Open Source Classifier for the Neonatal EEG Background: A Systematic Feature-Based Approach From Expert Scoring to Clinical Visualization S Montazeri, E Pinchefsky, I Tse, V Marchi, J Kohonen, M Kauppila, ... Frontiers in Human Neuroscience 18, 1417744, 0 | | |
Sampsa VanhataloHelsinki University, Children's HospitalVerified email at helsinki.fi
