| Deep recurrent model for individualized prediction of Alzheimer’s disease progression W Jung, E Jun, HI Suk, Alzheimer’s Disease Neuroimaging Initiative NeuroImage 237, 118143, 2021 | 39 | 2021 |
| Unified modeling of imputation, forecasting, and prediction for ad progression W Jung, AW Mulyadi, HI Suk Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 16 | 2019 |
| A deep generative–discriminative learning for multimodal representation in imaging genetics W Ko, W Jung, E Jeon, HI Suk IEEE Transactions on Medical Imaging 41 (9), 2348-2359, 2022 | 13 | 2022 |
| Estimating explainable Alzheimer’s disease likelihood map via clinically-guided prototype learning AW Mulyadi, W Jung, K Oh, JS Yoon, KH Lee, HI Suk NeuroImage 273, 120073, 2023 | 11* | 2023 |
| Inter-regional High-Level Relation Learning from Functional Connectivity via Self-supervision W Jung, DW Heo, E Jeon, J Lee, HI Suk International Conference on Medical Image Computing and Computer-Assisted …, 2021 | 9 | 2021 |
| Fine-grained attention for weakly supervised object localization J Sohn, E Jeon, W Jung, E Kang, HI Suk arXiv preprint arXiv:2104.04952, 2021 | 4 | 2021 |
| Deep joint learning of pathological region localization and Alzheimer’s disease diagnosis C Park, W Jung, HI Suk Scientific reports 13 (1), 11664, 2023 | 2 | 2023 |
| Deep Geometrical Learning for Alzheimer’s Disease Progression Modeling S Jeong, W Jung, J Sohn, HI Suk 2022 IEEE International Conference on Data Mining (ICDM), 2022 | 2 | 2022 |
| ENGINE: Enhancing neuroimaging and genetic information by neural embedding W Ko, W Jung, E Jeon, AW Mulyadi, HI Suk 2021 IEEE International Conference on Data Mining (ICDM), 1162-1167, 2021 | 2 | 2021 |
| Enhanced Functional-Connectivity Representation by Contrastive Learning for Brain Disease Diagnosis W Jung, HI Suk Organization for Human Brain Mapping (OHBM), 2024 | | 2024 |
| EAG-RS: A Novel Explainability-guided ROI-Selection Framework for ASD Diagnosis via Inter-regional Relation Learning W Jung, E Jeon, E Kang, HI Suk IEEE Transactions on Medical Imaging, 2023 | | 2023 |
| Module of Axis-based Nexus Attention for weakly supervised object localization J Sohn, E Jeon, W Jung, E Kang, HI Suk Scientific reports 13 (1), 18588, 2023 | | 2023 |
| Deep learning model for individualized trajectory prediction of clinical outcomes in mild cognitive impairment W Jung, SE Kim, JP Kim, H Jang, CJ Park, HJ Kim, DL Na, SW Seo, ... International Conference of the Korean Dementia Association (IC-KDA), 2023 | | 2023 |
| EAG-RS: A Novel Explainability-guided ROI-Selection Framework for ASD Diagnosis via Inter-regional Relation Learning W Jung, E Jeon, E Kang, HI Suk arXiv preprint arXiv:2310.03404, https://arxiv.org/abs/2310.03404, 2023 | | 2023 |
| Deep Geometric Learning with Monotonicity Constraints for Alzheimer's Disease Progression S Jeong, W Jung, J Sohn, HI Suk arXiv preprint arXiv:2310.03353, 2023 | | 2023 |
| A Quantitatively Interpretable Model for Alzheimer's Disease Prediction Using Deep Counterfactuals K Oh, DW Heo, AW Mulyadi, W Jung, E Kang, KH Lee, HI Suk arXiv preprint arXiv:2310.03457, 2023 | | 2023 |
| Predictive Modeling of Personalized Clinical Outcome Trajectories in Mild Cognitive Impairment W Jung, SE Kim, JP Kim, H Jang, CJ Park, HJ Kim, DL Na, SW Seo, ... International Conference of the Korean Dementia Association, 2023 | | 2023 |
| Quantifying Explainability of Counterfactual-Guided MRI Feature for Alzheimer's Disease Prediction K Oh, DW Heo, AW Mulyadi, W Jung, E Kang, HI Suk Medical Imaging Meets NeurIPS (MedNeurIPS) Workshop, 2022 | | 2022 |
| Clinically-guided Prototype Learning and Its Use for Explanation in Alzheimer's Disease Identification AW Mulyadi, W Jung, K Oh, JS Yoon, HI Suk Medical Imaging Meets NeurIPS (MedNeurIPS) Workshop, 2022 | | 2022 |
| Deep Counterfactual-Guided MRI Feature Representation and Quantitatively Interpretable Alzheimer’s Disease Prediction K Oh, DW Heo, AW Mulyadi, W Jung, E Kang, KH Lee, HI Suk | | 2022 |
Heung-Il SukDept. of Artificial Intelligence, Dept. of Brain and Cognitive Engineering, Koreakorea.ac.kr의 이메일 확인됨
