Congratulations!!! Wooyeol’s paper “Prototype-Guided Contrastive Knowledge Graph Representation Learning for Diagnosis Prediction” presented at ICPRAI2024 is selected as the 2nd best paper...
arXiv
- K. Oh, E. Jeon, D.W. Heo, Y. Shin, and H.-I. Suk, “FIESTA: Fourier-Based Semantic Augmentation with Uncertainty Guidance for Enhanced Domain Generalizability in Medical Image Segmentation,” arXiv:2406.14308, 2024. [paper]
- K. Oh*, J. Lee*, D.W. Heo, D. Shen, and H.-I. Suk, “Transferring Ultrahigh-Field Representations for Intensity-Guided Brain Segmentation of Low-Field Magnetic Resonance Imaging,” arXiv:2402.08409, 2024. (*: equally contributed) [paper]
- A. W. Mulyadi and H.-I. Suk, “KindMed: Knowledge-Induced Medicine Prescribing Network for Medication Recommendation,” arXiv:2310.14552, 2023. [paper]
- J.S. Yoon, K. Oh, Y. Shin, M. A. Mazurowski, and H.-I. Suk, “Domain Generalization for Medical Image Analysis: A Survey,” arXiv:2310.08598, 2023. [paper]
- K. Oh, D.-W. Heo, A. W. Mulyadi, W. Jung, E. Kang, K.H. Lee, and H.-I. Suk, “A Quantitatively Interpretable Model for Alzheimer’s Disease Prediction Using Deep Counterfactuals,” Research Square, 2022 [paper]; arXiv:2310.03457, 2023. [code]/[paper]
2024
Journal
![Frontiers"](https://milab.korea.ac.kr/wordpress/wp-content/uploads/2024/06/스크린샷-2024-06-04-18-22-37.png)
W. Ko, S. Jeong, S. K. Song, and H.-I. Suk, "EEG-Oriented Self-Supervised Learning with Triple Information Pathways Network," IEEE Transactions on Cybernetics, 2024. (2023-JCR-IF: 9.4, COMPUTER SCIENCE, ARTIFICIAL INTERLLIGENCE: 16/197, COMPUTER SCIENCE, CYBERNETICS: 2/32, AUTOMATION & CONTROL SYSTEMS: 4/84)
![Frontiers"](https://milab.korea.ac.kr/wordpress/wp-content/uploads/2024/04/2024_TNNLS.png)
S. Jeong*, W. Jung*, J. Sohn, and H.-I. Suk, "Deep Geometric Learning with Monotonicity Constraints for Alzheimer's Disease Progression," IEEE Transactions on Neural Networks and Learning Systems, 2024. (2023-JCR-IF: 10.2, COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE: 13/197, COMPUTER SCIENCE, THEORY & METHODS: 7/143, ENGINEERING, ELECTRICAL & ELECTRONIC: 11/352) (*: equally contributed)
![Frontiers"](https://milab.korea.ac.kr/wordpress/wp-content/uploads/2024/04/2024_Frontiers.png)
W. Jung*, S.E. Kim*, J Kim, H. Jang, C.J. Park, H.J. Kim, D.L. Na, S.W. Seo†, and H.-I. Suk†, “Deep Learning Model for Individualized Trajectory Prediction of Clinical Outcomes in Mild Cognitive Impairment,” Frontiers in Aging Neuroscience, 2024. (2023-JCR-IF: 4.1) (*: Equally contributed, †: co-corresponding)
Conference
- W. Park, A. W. Mulyadi, E. Kang, and H.-I. Suk, “Prototype-Guided Contrastive Knowledge Graph Representation Learning for Diagnosis Prediction,” International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI), Jeju Island, Korea, July 3-6, 2024.
- W. Jung and H.-I. Suk, “Enhanced Functional Connectivity Representation by Contrastive Learning for Brain Disease Diagnosis,” Organization for Human Brain Mapping (OHBM), Seoul, Korea, June 23-27, 2024
- J. Kim, S. Jeong, J. Jeon, and H.-I. Suk, “Unveiling Diagnostic Potential: EEG Microstate Representation Model for Alzheimer’s Disease and Frontotemporal Dementia,” 12th International Winter Conference on Brain-Computer Interface (BCI), High1 Resort, Korea, February 26-28, 2024.
- S. Jo, S. Jeong, J. Jeon, and H.-I. Suk, “Enhancing EEG Domain Generalization via Weighted Contrastive Learning,” 12th International Winter Conference on Brain-Computer Interface (BCI), High1 Resort, Korea, February 26-28, 2024.
- J. Lee, E. Kang, J. Maeng, and H.-I. Suk, “Eigendecomposition-Based Spatial-Temporal Attention for Brain Cognitive States Identification,” In ICASSP 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Seoul, Korea, April 14-19, 2024 (Oral presentation).
2023
Journal
![ALearnableCounterCondition"](https://milab.korea.ac.kr/wordpress/wp-content/uploads/2023/11/schizophrenia.png)
W.-S. Kim#, D.-W. Heo#, J. Maeng, J. Shen, U. Tsogt, S. Odkhuu, X. Zhang, S. Cheraghi, S.-W. Kim, B.-J. Ham, F.Z. Rami, J. Sui, C.Y. Kang, H.-I. Suk*, and Y.-C. Chung*, "Deep Learning-based Brain Age Prediction in Patients with Schizophrenia Spectrum Disorders," Schizophrenia Bulletin, December, 2023. (2022-JCR-IF: 6.6, PSYCHIATRY: 32/155) (*: Co-first, *: Co-corresponding)
![ALearnableCounterCondition"](https://milab.korea.ac.kr/wordpress/wp-content/uploads/2023/11/A-Learnable-Counter-condition-Analysis-Framework-for-Functional-Connectivity-based-Neurological-Disorder-Diagnosis.jpg)
E. Kang, D. Heo, J. Lee, and H.-I. Suk, "A Learnable Counter-condition Analysis Framework for Functional Connectivity-based Neurological Disorder Diagnosis," IEEE Transactions on Medical Imaging, 2023. (2022-JCR-IF: 10.6, COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS: 6/110)
![EAG-RS"](https://milab.korea.ac.kr/wordpress/wp-content/uploads/2023/11/EAG-RS_overallframework.jpg)
W. Jung, E. Jeon, E. Kang, and H.-I. Suk, "EAG-RS: A Novel Explainability-guided ROI-Selection Framework for ASD Diagnosis via Inter-regional Relation Learning," IEEE Transactions on Medical Imaging, 2023. (2022-JCR-IF: 10.6, COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS: 6/110)
![MoANA"](https://milab.korea.ac.kr/wordpress/wp-content/uploads/2023/10/2023_junghyo.png)
J. Sohn, E. Jeon, W. Jung, E. Kang, and H.-I. Suk, “Module of Axis-based Nexus Attention for Weakly Supervised Object Localization,” Scientific Reports, Vol. 13, No. 18588, October, 2023. (2022-JCR-IF: 4.6, MULTIDISCIPLINARY SCIENCES 22/73)
![Deep](https://milab.korea.ac.kr/wordpress/wp-content/uploads/2023/09/DeepEfficientContinuousManifoldLearningforTimeSeriesModeling.jpg)
S. Jeong, W. Ko, A. W. Mulyadi, and H.-I. Suk, “Deep Efficient Continuous Manifold Learning for Time Series Modeling,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 46, No. 1, pp. 171-184, January, 2024. (Early Access: September, 2023)(2022-JCR-IF: 23.6, COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE: 2/145, ENGINEERING, ELECTRICAL & ELECTRONIC: 2/275)
![Spatiotemporal Graph Neural Networks for Predicting Mid-to-Long-Term PM2.5 Concentrations](https://milab.korea.ac.kr/wordpress/wp-content/uploads/2023/09/dykim.png)
D.-Y. Kim, D.-Y. Jin, and H.-I. Suk, “Spatiotemporal graph neural networks for predicting mid-to-long-term PM2.5 concentrations,” Journal of Cleaner Production, Vol. 425, p. 138880, September, 2023. (Early Access: September, 2023)(2022-JCR-IF: 11.1, ENVIRONMENTAL SCIENCES: 22/274)
![Site-Invariant Meta-Modulation Learning for Multi-Site Autism Spectrum Disorders Diagnosis](https://milab.korea.ac.kr/wordpress/wp-content/uploads/2023/08/site_invariant.png)
J. Lee, E. Kang, D.-W. Heo, and H.-I. Suk, “Site-invariant meta-modulation learning for multisite autism spectrum disorders diagnosis,” IEEE Transactions on Neural Networks and Learning Systems, early access, September, 2023. (2022-JCR-IF: 10.4, COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE: 14/145, COMPUTER SCIENCE, HARDWARE & ARCHITECTURE: 3/54)
![Medical Transformer: Universal Brain Encoder for 3D MRI Analysis](https://milab.korea.ac.kr/wordpress/wp-content/uploads/2023/08/스크린샷-2023-08-09-오후-12.58.13.png)
E. Jun, S. Jeong, D.-W. Heo, and H.-I. Suk, “Medical transformer: Universal encoder for 3-D brain MRI analysis,” IEEE Transactions on Neural Networks and Learning Systems, early access, September, 2023. (2022-JCR-IF: 10.4, COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE: 14/145, COMPUTER SCIENCE, HARDWARE & ARCHITECTURE: 3/54)
![Deep Joint Learning of Pathological Region Localization and Alzheimer's Disease Diagnosis](https://milab.korea.ac.kr/wordpress/wp-content/uploads/2023/07/2023_ScientificReport.png)
C. Park*, W. Jung*, and H.-I. Suk, “Deep joint learning of pathological region localization and alzheimer’s disease diagnosis,” Scientific Reports, Vol. 13, No. 11664, 2023. (2021-JCR-IF: 4.997, MULTIDISCIPLINARY SCIENCES: 22/73)(*: Equally contributed)
![Estimating Explainable Alzheimer’s Disease Likelihood Map via Clinically-guided Prototype Learning](https://milab.korea.ac.kr/wordpress/wp-content/uploads/2023/03/xadlime-2048x759.png)
A. W. Mulyadi, W. Jung, K. Oh, J. S. Yoon, K. H. Lee, and H.-I. Suk, “Estimating Explainable Alzheimer’s Disease Likelihood Map via Clinically-guided Prototype Learning,” NeuroImage, Vol. 273, p. 120073, June, 2023. (2021-JCR-IF: 7.400, NEUROSCIENCES: 38/275, NEUROIMAGING: 2/14, RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING: 15/136)
![](https://milab.korea.ac.kr/wordpress/wp-content/uploads/2023/04/2023_ER.png)
J.Y. Choi, S.S. Lee, N.Y. Kim, H.J. Park, Y.S. Sung, Y. Lee, J.S. Yoon, and H.-I. Suk, "The Effect of Hepatic Steatosis on Liver Volume Determined by Proton Density Fat Fraction and Deep Learning–Measured Liver Volume," European Radiology, pp. 1-9, April, 2023 (2021-JCR-IF: 7.034).
![](https://milab.korea.ac.kr/wordpress/wp-content/uploads/2023/04/2023_IJN.png)
W.-S. Kim, D.-W. Heo, J. Shen, U. Tsogt, S. Odkhuu, S.-W. Kim, H.-I. Suk, B.-J. Ham, F.Z. Rami, C.Y. Kang, J. Sui, and Y.-C. Chung, "Stage-Specific Brain Aging in First-Episode Schizophrenia and Treatment-Resistant Schizophrenia," International Journal of Neuropsychopharmacology, Vol. 26, No. 3, pp. 207-216, March 2023 (2021-JCR-IF: 5.310).
Conference
- Y. Shin, J. Maeng, K. Oh, and H.-I. Suk, “Frequency Mixup Manipulation based Unsupervised Domain Adaptation for Brain Disease Identification,” 7th Asian Conference on Pattern Recognition (ACPR 2023), Kitakyushu, Japan, November 5-8, 2023 (Oral Presentation). [code]
- J. Maeng†, K. Oh†, and H.-I. Suk, “Age-Aware Guidance via Masking-Based Attention in Face Aging,” 32nd ACM International Conference on Information and Knowledge Management (CIKM), Birmingham, UK, October 21-25, 2023 (†: equally contributed). [code]
- J.S. Yoon, C. Zhang, H.-I. Suk, J. Guo, X. Li, “SADM: Sequence-Aware Diffusion Model for Longitudinal Medical Image Generation,” Information Processing in Medical Imaging (IPMI), 2023
- S. Jo†, J. Jeon†, S. Jeong, and H.-I. Suk, “Channel-Aware Self-Supervised Learning for EEG-based BCI,” 11th International Winter Conference on Brain-Computer Interface (BCI), High1 Resort, Korea, February 20-22, 2023 (†: equally contributed).
- S. Jeong, E. Jeon, S. Noh, J. Lee, H. Kim, S. Kim, and H.-I. Suk, “Learning-based Sleep Quality Evaluation,” 11th International Winter Conference on Brain-Computer Interface (BCI), High1 Resort, Korea, February 20-22, 2023.