| Deep multi-task learning for interpretable glaucoma detection N Mojab, V Noroozi, SY Philip, JA Hallak 2019 IEEE 20th International conference on information reuse and integration …, 2019 | 23 | 2019 |
| Leveraging semi-supervised learning for fairness using neural networks V Noroozi, S Bahaadini, S Sheikhi, N Mojab, SY Philip 2019 18th IEEE International Conference On Machine Learning And Applications …, 2019 | 15 | 2019 |
| Real-world multi-domain data applications for generalizations to clinical settings N Mojab, V Noroozi, D Yi, MP Nallabothula, A Aleem, SY Philip, JA Hallak 2020 19th IEEE International Conference on Machine Learning and Applications …, 2020 | 8 | 2020 |
| CvS: Classification via Segmentation For Small Datasets N Mojab, PS Yu, JA Hallak, D Yi In Proceedings of the British Machine Vision Conference, London, UK, 21–24 …, 2021 | 3 | 2021 |
| I-ODA, Real-World Multi-modal Longitudinal Data for OphthalmicApplications N Mojab, V Noroozi, A Aleem, MP Nallabothula, J Baker, DT Azar, ... Proceedings of the 14th International Joint Conference on Biomedical …, 2021 | 2 | 2021 |
| FundusNet, A self-supervised contrastive learning framework for Fundus Feature Learning N Mojab, M Alam, J Hallak Investigative Ophthalmology & Visual Science 63 (7), 188–F0035-188–F0035, 2022 | | 2022 |
| Cvs: Classification via segmentation for small datasets N Mojab, PS Yu, JA Hallak, D Yi arXiv preprint arXiv:2111.00042, 2021 | | 2021 |
| Deep Learning for Medical Imaging Applications N Mojab University of Illinois at Chicago, 2021 | | 2021 |
| Detecting Glaucoma and Suspect Progression through Longitudinal Fundus Photos J Hallak, N Mojab, J Baker, V Noroozi, DT Azar, M Rosenblatt Investigative Ophthalmology & Visual Science 60 (9), 1472-1472, 2019 | | 2019 |
| Longitudinal Data in Ophthalmic Imaging: Curation and Annotation J Hallak, D Yi, V Noorozi, C Lam, N Mojab, J Baker, D Rubin, DT Azar, ... Investigative Ophthalmology & Visual Science 59 (9), 1721-1721, 2018 | | 2018 |
