2 citations · 4 across the 9 of their papers we have counts for
10 papers
SMI: Ontology-Grounded Semantic IDs for Hierarchy-Aware Medical Concept Representation
Ziyang Song, Lia Shen, Yixuan Li +6
Biomedical language models (LMs) provide strong representations for clinical tasks, but they often fail to capture the hierarchical structure among medical concepts. This limitatio…
FedEHR-Agents: Federated Agentic Optimization for Automated EHR Modeling
Jun Bai, Ruilin Wang, Yue Li
Recent advances in large language models are enabling autonomous clinical agents to perform increasingly complex electronic health record (EHR) modeling workflows. However, agents…
DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data
Ruilin Wang, Bo-Hong Wang, Elizabeth Kourbatski +6
Clinical machine learning (ML) has the potential to support high-stakes medical decision-making, but reliable deployment is often constrained by scarce, heterogeneous, and temporal…
ChatHealthAI: Aligning Electronic Health Record Representations with Large Language Models for Grounded Clinical Reasoning
Bo-Hong Wang, Baicheng Peng, Ruilin Wang +3
Large language models (LLMs) exhibit strong natural-language reasoning abilities for clinical decision support, but struggle to effectively model structured longitudinal electronic…
FedEHR-Gen: Federated Synthetic Time-Series EHR Generation via Latent Space Alignment and Distribution-Aware Aggregation
Jun Bai, Ziyang Song, Yue Li
Synthetic Electronic Health Record (EHR) generation provides a promising avenue for data augmentation and cross-hospital modeling in privacy-constrained healthcare settings. Howeve…
Sketch Then Paint: Hierarchical Reinforcement Learning for Diffusion Multi-Modal Large Language Models
Siqi Luo, Jianghan Shen, Yi Xin +9
Diffusion Multi-Modal Large Language Models (dMLLMs) are powerful for image generation, but optimizing them through reinforcement learning (RL) remains a major challenge. One prima…
MixEHR-Nest: Identifying Subphenotypes within Electronic Health Records through Hierarchical Guided-Topic Modeling
Ruohan Wang, Zilong Wang, Ziyang Song +2
Automatic subphenotyping from electronic health records (EHRs)provides numerous opportunities to understand diseases with unique subgroups and enhance personalized medicine for pat…
TrajGPT: Irregular Time-Series Representation Learning for Health Trajectory Analysis
Ziyang Song, Qingcheng Lu, He Zhu +2
In many domains, such as healthcare, time-series data is often irregularly sampled with varying intervals between observations. This poses challenges for classical time-series mode…
Bidirectional Generative Pre-training for Improving Healthcare Time-series Representation Learning
Ziyang Song, Qincheng Lu, He Zhu +2
Learning time-series representations for discriminative tasks, such as classification and regression, has been a long-standing challenge in the healthcare domain. Current pre-train…
TimelyGPT: Extrapolatable Transformer Pre-training for Long-term Time-Series Forecasting in Healthcare
Ziyang Song, Qincheng Lu, Hao Xu +3
Large-scale pre-trained models (PTMs) such as BERT and GPT have recently achieved great success in Natural Language Processing and Computer Vision domains. However, the development…