activity
20242026
most citedEHR-R1: A Reasoning-Enhanced Foundational Language Model for Electronic Health Record Analysis

1 citations · 2 across the 12 of their papers we have counts for

collaborators

13 papers

q-bio.NC2026

Predicting Neuromodulation Outcome for Parkinson's Disease with Generative Virtual Brain Model

Siyuan Du, Siyi Li, Shuwei Bai +10

Parkinson's disease (PD) affects over ten million people worldwide. Although temporal interference (TI) and deep brain stimulation (DBS) are promising therapies, inter-individual v…

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.CL2025★ 1 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

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…

cs.CV2025

Boosting Pathology Foundation Models via Few-shot Prompt-tuning for Rare Cancer Subtyping

Dexuan He, Xiao Zhou, Wenbin Guan +11

Rare cancers comprise 20-25% of all malignancies but face major diagnostic challenges due to limited expert availability-especially in pediatric oncology, where they represent over…

cs.CV2025

SceneGen: Single-Image 3D Scene Generation in One Feedforward Pass

Yanxu Meng, Haoning Wu, Ya Zhang +1

3D content generation has recently attracted significant research interest, driven by its critical applications in VR/AR and embodied AI. In this work, we tackle the challenging ta…

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.CV2025

SpatialScore: Towards Comprehensive Evaluation for Spatial Intelligence

Haoning Wu, Xiao Huang, Yaohui Chen +3

Existing evaluations of multimodal large language models (MLLMs) on spatial intelligence are typically fragmented and limited in scope. In this work, we aim to conduct a holistic a…

cs.CV2025

Multi-Agent System for Comprehensive Soccer Understanding

Jiayuan Rao, Zifeng Li, Haoning Wu +3

Recent advances in soccer understanding have demonstrated rapid progress, yet existing research predominantly focuses on isolated or narrow tasks. To bridge this gap, we propose a…

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…

cs.CV2025★ 1 cited

M^3Builder: A Multi-Agent System for Automated Machine Learning in Medical Imaging

Jinghao Feng, Qiaoyu Zheng, Chaoyi Wu +4

Agentic AI systems have gained significant attention for their ability to autonomously perform complex tasks. However, their reliance on well-prepared tools limits their applicabil…

eess.IV2024

Knowledge-enhanced Pretraining for Vision-language Pathology Foundation Model on Cancer Diagnosis

Xiao Zhou, Luoyi Sun, Dexuan He +10

Vision-language foundation models have shown great promise in computational pathology but remain primarily data-driven, lacking explicit integration of medical knowledge. We introd…