15 papers
Domain Adaptation Targeting Heterogeneous and Imbalanced Subgroups
Doudou Zhou, Mengyan Li, Yun Wang +2
Domain adaptation enables generalizable and efficient data-driven research. However, existing work has largely focused on domain adaptation for some intrinsically homogeneous targe…
Contrastive Learning on Multimodal Analysis of Electronic Health Records
Tianxi Cai, Feiqing Huang, Ryumei Nakada +2
Electronic health record (EHR) systems capture a wealth of multimodal clinical data, encompassing both structured clinical codes and unstructured clinical notes. Yet, many EHR-focu…
Spherical Mixture Integration for Latent Embedding Alignment across Multi-Source Feature Spaces
Yuming Zhang, Congyuan Duan, Dong Xia +2
Multi-institutional electronic health record (Multi-EHR) data have emerged as a powerful resource for developing predictive models to support clinical decisions and for generating…
Structured Transfer Learning for Survival Risk Stratification in Data-Sparse Clinical Cohorts
Junhan Yu, Yurui Chen, Juan Delgado-SanMartin +3
Background: Survival prediction models are often less reliable in clinical groups with limited sample sizes or few outcome events. Target-only models may be unstable, whereas model…
Cost-optimal Sequential Testing via Doubly Robust Q-learning
Doudou Zhou, Yiran Zhang, Dian Jin +3
Clinical decision-making often involves selecting tests that are costly, invasive, or time-consuming, motivating individualized, sequential strategies for what to measure and when…
Hierarchical Contrastive Learning for Multimodal Data
Huichao Li, Junhan Yu, Doudou Zhou
Multimodal representation learning is commonly built on a shared-private decomposition, treating latent information as either common to all modalities or specific to one. This bina…