6 papers
Domain Generalization under Sampling Pattern Shifts in Irregular Time Series
Changhun Kim, Joohyung Lee, Kwanhyung Lee +3
Irregularly sampled multivariate time series (ISMTS) are prevalent in real-world applications, where both observation times and available measurements can vary substantially across…
Learning to Select Source-Traceable Evidence for Language-Model Prediction from Irregular Clinical Time Series
Kwanhyung Lee, Juhwan Choi, Jongheon Kim +5
Numerical time-series models effectively process irregular electronic health record (EHR) trajectories, but do not expose which temporal patterns support each prediction as readabl…
Structure-Aware Set Transformers: Temporal and Variable-Type Attention Biases for Asynchronous Clinical Time Series
Joohyung Lee, Kwanhyung Lee, Changhun Kim +1
Electronic health records (EHR) are irregular, asynchronous multivariate time series. As time-series foundation models increasingly tokenize events rather than discretizing time, t…
Soft Equivariance Regularization for Invariant Self-Supervised Learning
Joohyung Lee, Changhun Kim, Hyunsu Kim +2
Self-supervised learning (SSL) typically learns representations invariant to semantic-preserving augmentations. While effective for recognition, enforcing strong invariance can sup…
EMR-AGENT: Automating Cohort and Feature Extraction from EMR Databases
Kwanhyung Lee, Sungsoo Hong, Joonhyung Park +4
Machine learning models for clinical prediction rely on structured data extracted from Electronic Medical Records (EMRs), yet this process remains dominated by hardcoded, database-…
ReviewScore: Misinformed Peer Review Detection with Large Language Models
Hyun Ryu, Doohyuk Jang, Hyemin S. Lee +16
Peer review serves as a backbone of academic research, but in most AI conferences, the review quality is degrading as the number of submissions explodes. To reliably detect low-qua…