activity
20242026
most citedChestX-Reasoner: Advancing Radiology Foundation Models with Reasoning through Step-by-Step Verification

2 citations · 4 across the 4 of their papers we have counts for

collaborators

8 papers

cs.CV2026

PhenoLIP: Integrating Phenotype Ontology Knowledge into Medical Vision-Language Pretraining

Cheng Liang, Chaoyi Wu, Weike Zhao +3

Recent progress in large-scale CLIP-like vision-language models(VLMs) has greatly advanced medical image analysis. However, most existing medical VLMs still rely on coarse image-te…

cs.CL20251 cited

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…

cs.CL2025

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…

cs.AI20252 cited

ChestX-Reasoner: Advancing Radiology Foundation Models with Reasoning through Step-by-Step Verification

Ziqing Fan, Cheng Liang, Chaoyi Wu +3

Recent advances in reasoning-enhanced large language models (LLMs) and multimodal LLMs (MLLMs) have significantly improved performance in complex tasks, yet medical AI models often…

cs.CL2025

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…

cs.CV2025

RadIR: A Scalable Framework for Multi-Grained Medical Image Retrieval via Radiology Report Mining

Tengfei Zhang, Ziheng Zhao, Chaoyi Wu +4

Developing advanced medical imaging retrieval systems is challenging due to the varying definitions of `similar images' across different medical contexts. This challenge is compoun…