| MRI breast tumor segmentation using different encoder and decoder CNN architectures M El Adoui, SA Mahmoudi, MA Larhmam, M Benjelloun Computers 8 (3), 52, 2019 | 100 | 2019 |
| Multi-input deep learning architecture for predicting breast tumor response to chemotherapy using quantitative MR images M El Adoui, S Drisis, M Benjelloun International journal of computer assisted radiology and surgery 15, 1491-1500, 2020 | 64 | 2020 |
| Automated breast tumor segmentation in DCE-MRI using deep learning M Benjelloun, M El Adoui, MA Larhmam, SA Mahmoudi 2018 4th International Conference on Cloud Computing Technologies and …, 2018 | 52 | 2018 |
| Internet of things: learning and practices. application to smart city O Debauche, S Mahmoudi, SA Mahmoudi 2018 4th International Conference on Cloud Computing Technologies and …, 2018 | 30 | 2018 |
| A PRM approach for early prediction of breast cancer response to chemotherapy based on registered MR images M El Adoui, S Drisis, M Benjelloun International journal of computer assisted radiology and surgery 13, 1233-1243, 2018 | 24 | 2018 |
| Deep learning-based prediction of response to HER2-targeted neoadjuvant chemotherapy from pre-treatment dynamic breast MRI: a multi-institutional validation study N Braman, ME Adoui, M Vulchi, P Turk, M Etesami, P Fu, K Bera, S Drisis, ... arXiv preprint arXiv:2001.08570, 2020 | 21 | 2020 |
| Towards breast cancer response prediction using artificial intelligence and radiomics Y Amkrane, M El Adoui, M Benjelloun 2020 5th International Conference on Cloud Computing and Artificial …, 2020 | 20 | 2020 |
| Breast Cancer Heterogeneity Analysis as Index of Response to Treatment Using MRI Images: A Review M El Adoui, S Drisis, MA Larhmam, M Lemort, M Benjelloun Imaging in Medicine 9 (4), 109-119, 2017 | 20 | 2017 |
| Deep learning approach predicting breast tumor response to neoadjuvant treatment using DCE-MRI volumes acquired before and after chemotherapy M El Adoui, MA Larhmam, S Drisis, M Benjelloun Medical Imaging 2019: Computer-Aided Diagnosis 10950, 649-658, 2019 | 19 | 2019 |
| Predict breast tumor response to chemotherapy using a 3D deep learning architecture applied to DCE-MRI data M El Adoui, S Drisis, M Benjelloun Bioinformatics and Biomedical Engineering: 7th International Work-Conference …, 2019 | 16 | 2019 |
| Cloud-based platform for computer vision applications SA Mahmoudi, M El ADOUI, MA Belarbi, MA Larhmam, F Lecron ICSDE '17 Proceedings of the 2017 International Conference on Smart Digital …, 2017 | 11 | 2017 |
| Analyzing breast tumor heterogeneity to predict the response to chemotherapy using 3D MR images registration M EL ADOUI, S Drisis, M Benjelloun ICSDE '17: Proceedings of the 2017 International Conference on Smart Digital …, 2017 | 11 | 2017 |
| Early prediction of neoadjuvant treatment outcome in locally advanced breast cancer using parametric response mapping and radial heterogeneity from breast MRI. S Drisis, M El Adoui | 11* | |
| Development and external validation of a deep learning model for predicting response to HER2-targeted neoadjuvant therapy from pretreatment breast MRI. M Vulchi, M El Adoui, N Braman, P Turk, M Etesami, S Drisis, D Plecha, ... Journal of Clinical Oncology 37 (15_suppl), 593-593, 2019 | 9 | 2019 |
| Real time web-based toolbox for computer vision SA Mahmoudi, MA Belarbi, M El Adoui, MA Larhmam, F Lecron Journal of Science and Technology of the Arts 10 (2), 3-13, 2018 | 6 | 2018 |
| Composite score for anomaly detection in imbalanced real-world industrial dataset A Bougaham, M El Adoui, I Linden, B Frénay Machine Learning 113 (7), 4381-4406, 2024 | 3 | 2024 |
| New explainable deep CNN design for classifying breast tumor response over neoadjuvant chemotherapy ME Adoui, S Drisis, M Benjelloun Current Medical Imaging 19 (5), 526-533, 2023 | 3 | 2023 |
| Industrial and Medical Anomaly Detection Through Cycle-Consistent Adversarial Networks A Bougaham, V Delchevalerie, ME Adoui, B Frénay arXiv preprint arXiv:2302.05154, 2023 | 2 | 2023 |
| Prospective evaluation by Parametric Response Mapping (PRM) applied in MRI volumetric images of breast cancer M EL ADOUI, S Drisis, M Benjelloun | 1* | 2016 |
| Constrained Tiny Machine Learning for Predicting Gas Concentration with I4. 0 Low-cost Sensors M El Adoui, T Herpoel, B Frénay ACM Transactions on Embedded Computing Systems 23 (3), 1-23, 2024 | | 2024 |
Mohammed BENJELLOUNUniversity of MonsAdresse e-mail validée de umons.ac.be
