5 papers
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…
Your Dense Retriever is Secretly an Expeditious Reasoner
Yichi Zhang, Jun Bai, Zhixin Cai +4
Dense retrievers enhance retrieval by encoding queries and documents into continuous vectors, but they often struggle with reasoning-intensive queries. Although Large Language Mode…
CogAtom: From Cognitive Atoms to Olympiad-level Mathematical Reasoning in Large Language Models
Zhuofan Chen, Jiyuan He, Yichi Zhang +4
Mathematical reasoning poses significant challenges for Large Language Models (LLMs) due to its demand for multi-step reasoning and abstract conceptual integration. While recent te…