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Wonsik Jung
Wonsik Jung
Department of Brain and Cognitive Engineering, Korea University
Verified email at korea.ac.kr - Homepage
Title
Cited by
Cited by
Year
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
392021
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
162019
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
132022
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
92021
Fine-grained attention for weakly supervised object localization
J Sohn, E Jeon, W Jung, E Kang, HI Suk
arXiv preprint arXiv:2104.04952, 2021
42021
Deep joint learning of pathological region localization and Alzheimer’s disease diagnosis
C Park, W Jung, HI Suk
Scientific reports 13 (1), 11664, 2023
32023
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
22022
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
22021
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, ...
Frontiers in Aging Neuroscience, 2024
2024
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 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
BRAIN DISEASE PREDICTION APPARATUS AND METHOD, AND LEARNING APPARATUS FOR PREDICTING BRAIN DISEASE
HI Suk, W Jung
KR Patent App. 10-2021-7,022,211, 2021
2021
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Articles 1–20