91 citations · 236 across the 31 of their papers we have counts for
31 papers
STRIVE: Multi-Agent Structured Temporal Reasoning with Integrated Verification for Longitudinal Radiology Report Generation
Junyeong Maeng, Eunsong Kang, Heung-Il Suk
Longitudinal radiology report generation (LRRG) requires identifying both current findings and their changes relative to a prior study. Existing methods jointly model diagnosis, at…
HyFI: Hyperbolic Feature Interpolation for Brain-Vision Alignment
Sangmin Jo, Wootaek Jeong, Da-Woon Heo +2
Recent progress in artificial intelligence has encouraged numerous attempts to understand and decode human visual system from brain signals. These prior works typically align neura…
Permutation-Equivariant 2D State Space Models: Theory and Canonical Architecture for Multivariate Time Series
Seungwoo Jeong, Heung-Il Suk
Multivariate time series (MTS) modeling often implicitly imposes an artificial ordering over variables, violating the inherent exchangeability found in many real-world systems wher…
MEASURE: Multi-scale Minimal Sufficient Representation Learning for Domain Generalization in Sleep Staging
Sangmin Jo, Jee Seok Yoon, Wootaek Jeong +2
Deep learning-based automatic sleep staging has significantly advanced in performance and plays a crucial role in the diagnosis of sleep disorders. However, those models often stru…
IdenBAT: Disentangled Representation Learning for Identity-Preserved Brain Age Transformation
Junyeong Maeng, Kwanseok Oh, Wonsik Jung +1
Brain age transformation aims to convert reference brain images into synthesized images that accurately reflect the age-specific features of a target age group. The primary objecti…
DyMix: Dynamic Frequency Mixup Scheduler based Unsupervised Domain Adaptation for Enhancing Alzheimer's Disease Identification
Yooseung Shin, Kwanseok Oh, Heung-Il Suk
Advances in deep learning (DL)-based models for brain image analysis have significantly enhanced the accuracy of Alzheimer's disease (AD) diagnosis, allowing for more timely interv…
FIESTA: Fourier-Based Semantic Augmentation with Uncertainty Guidance for Enhanced Domain Generalizability in Medical Image Segmentation
Kwanseok Oh, Eunjin Jeon, Da-Woon Heo +2
Single-source domain generalization (SDG) in medical image segmentation (MIS) aims to generalize a model using data from only one source domain to segment data from an unseen targe…
Transferring Ultrahigh-Field Representations for Intensity-Guided Brain Segmentation of Low-Field Magnetic Resonance Imaging
Kwanseok Oh, Jieun Lee, Da-Woon Heo +2
Ultrahigh-field (UHF) magnetic resonance imaging (MRI), i.e., 7T MRI, provides superior anatomical details of internal brain structures owing to its enhanced signal-to-noise ratio…
A Quantitatively Interpretable Model for Alzheimer's Disease Prediction Using Deep Counterfactuals
Kwanseok Oh, Da-Woon Heo, Ahmad Wisnu Mulyadi +4
Deep learning (DL) for predicting Alzheimer's disease (AD) has provided timely intervention in disease progression yet still demands attentive interpretability to explain how their…
EAG-RS: A Novel Explainability-guided ROI-Selection Framework for ASD Diagnosis via Inter-regional Relation Learning
Wonsik Jung, Eunjin Jeon, Eunsong Kang +1
Deep learning models based on resting-state functional magnetic resonance imaging (rs-fMRI) have been widely used to diagnose brain diseases, particularly autism spectrum disorder…
Deep Geometric Learning with Monotonicity Constraints for Alzheimer's Disease Progression
Seungwoo Jeong, Wonsik Jung, Junghyo Sohn +1
Alzheimer's disease (AD) is a devastating neurodegenerative condition that precedes progressive and irreversible dementia; thus, predicting its progression over time is vital for c…
Knowledge-Induced Medicine Prescribing Network for Medication Recommendation
Ahmad Wisnu Mulyadi, Heung-Il Suk
Extensive adoption of electronic health records (EHRs) offers opportunities for their use in various downstream clinical analyses. To accomplish this purpose, enriching an EHR coho…
Domain Generalization for Medical Image Analysis: A Review
Jee Seok Yoon, Kwanseok Oh, Yooseung Shin +2
Medical image analysis (MedIA) has become an essential tool in medicine and healthcare, aiding in disease diagnosis, prognosis, and treatment planning, and recent successes in deep…
SADM: Sequence-Aware Diffusion Model for Longitudinal Medical Image Generation
Jee Seok Yoon, Chenghao Zhang, Heung-Il Suk +2
Human organs constantly undergo anatomical changes due to a complex mix of short-term (e.g., heartbeat) and long-term (e.g., aging) factors. Evidently, prior knowledge of these fac…
XADLiME: eXplainable Alzheimer's Disease Likelihood Map Estimation via Clinically-guided Prototype Learning
Ahmad Wisnu Mulyadi, Wonsik Jung, Kwanseok Oh +2
Diagnosing Alzheimer's disease (AD) involves a deliberate diagnostic process owing to its innate traits of irreversibility with subtle and gradual progression. These characteristic…
TransSleep: Transitioning-aware Attention-based Deep Neural Network for Sleep Staging
Jauen Phyo, Wonjun Ko, Eunjin Jeon +1
Sleep staging is essential for sleep assessment and plays a vital role as a health indicator. Many recent studies have devised various machine learning as well as deep learning arc…
Deep Efficient Continuous Manifold Learning for Time Series Modeling
Seungwoo Jeong, Wonjun Ko, Ahmad Wisnu Mulyadi +1
Modeling non-Euclidean data is drawing extensive attention along with the unprecedented successes of deep neural networks in diverse fields. Particularly, a symmetric positive defi…
Learn-Explain-Reinforce: Counterfactual Reasoning and Its Guidance to Reinforce an Alzheimer's Disease Diagnosis Model
Kwanseok Oh, Jee Seok Yoon, Heung-Il Suk
Existing studies on disease diagnostic models focus either on diagnostic model learning for performance improvement or on the visual explanation of a trained diagnostic model. We p…
Deep Joint Learning of Pathological Region Localization and Alzheimer's Disease Diagnosis
Changhyun Park, Heung-Il Suk
The identification of Alzheimer's disease (AD) and its early stages using structural magnetic resonance imaging (MRI) has been attracting the attention of researchers. Various data…
Medical Transformer: Universal Brain Encoder for 3D MRI Analysis
Eunji Jun, Seungwoo Jeong, Da-Woon Heo +1
Transfer learning has gained attention in medical image analysis due to limited annotated 3D medical datasets for training data-driven deep learning models in the real world. Exist…
Fine-Grained Attention for Weakly Supervised Object Localization
Junghyo Sohn, Eunjin Jeon, Wonsik Jung +2
Although recent advances in deep learning accelerated an improvement in a weakly supervised object localization (WSOL) task, there are still challenges to identify the entire body…
Multi-view Integration Learning for Irregularly-sampled Clinical Time Series
Yurim Lee, Eunji Jun, Heung-Il Suk
Electronic health record (EHR) data is sparse and irregular as it is recorded at irregular time intervals, and different clinical variables are measured at each observation point.…
Born Identity Network: Multi-way Counterfactual Map Generation to Explain a Classifier's Decision
Kwanseok Oh, Jee Seok Yoon, Heung-Il Suk
There exists an apparent negative correlation between performance and interpretability of deep learning models. In an effort to reduce this negative correlation, we propose a Born…
A Novel RL-assisted Deep Learning Framework for Task-informative Signals Selection and Classification for Spontaneous BCIs
Wonjun Ko, Eunjin Jeon, Heung-Il Suk
In this work, we formulate the problem of estimating and selecting task-relevant temporal signal segments from a single EEG trial in the form of a Markov decision process and propo…