1 citations · 2 across the 2 of their papers we have counts for
6 papers · 1 filter
EHR-R1: A Reasoning-Enhanced Foundational Language Model for Electronic Health Record Analysis
Yusheng Liao, Chaoyi Wu, Junwei Liu +12
Electronic Health Records (EHRs) contain rich yet complex information, and their automated analysis is critical for clinical decision-making. Despite recent advances of large langu…
Evolving Interactive Diagnostic Agents in a Virtual Clinical Environment
Pengcheng Qiu, Chaoyi Wu, Junwei Liu +11
We present a framework for training large language models (LLMs) as diagnostic agents with reinforcement learning, enabling them to manage multi-turn interactive diagnostic process…
End-to-End Agentic RAG System Training for Traceable Diagnostic Reasoning
Qiaoyu Zheng, Yuze Sun, Chaoyi Wu +8
The integration of Large Language Models (LLMs) into healthcare is constrained by knowledge limitations, hallucinations, and a disconnect from Evidence-Based Medicine (EBM). While…
An Agentic System for Rare Disease Diagnosis with Traceable Reasoning
Weike Zhao, Chaoyi Wu, Yanjie Fan +10
Rare diseases affect over 300 million individuals worldwide, yet timely and accurate diagnosis remains an urgent challenge. Patients often endure a prolonged diagnostic odyssey exc…
Quantifying the Reasoning Abilities of LLMs on Real-world Clinical Cases
Pengcheng Qiu, Chaoyi Wu, Shuyu Liu +7
Recent advancements in reasoning-enhanced large language models (LLMs), such as DeepSeek-R1 and OpenAI-o3, have demonstrated significant progress. However, their application in pro…
Towards Evaluating and Building Versatile Large Language Models for Medicine
Chaoyi Wu, Pengcheng Qiu, Jinxin Liu +5
In this study, we present MedS-Bench, a comprehensive benchmark designed to evaluate the performance of large language models (LLMs) in clinical contexts. Unlike existing benchmark…