60 citations · 262 across the 28 of their papers we have counts for
28 papers
Evaluating Large Language Models in Dynamic Clinical Decision-Making with Standardized Patient Cases
Cheng Liang, Pengcheng Qiu, Ya Zhang +3
Large language models (LLMs) are increasingly proposed as clinical agents, yet static, single-turn benchmarks cannot capture how a model dynamically delivers care across an encount…
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…
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…
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…
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…
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…
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…
How Well Can Modern LLMs Act as Agent Cores in Radiology Environments?
Qiaoyu Zheng, Chaoyi Wu, Weike Zhao +5
Radiology, with its heterogeneous modalities, anatomies, and evolving protocols, is a natural yet high-stakes testbed for agentic AI. As LLMs grow more capable and tool ecosystems…
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…
AutoRG-Brain: Grounded Report Generation for Brain MRI
Jiayu Lei, Xiaoman Zhang, Chaoyi Wu +6
Radiologists are tasked with interpreting a large number of images in a daily base, with the responsibility of generating corresponding reports. This demanding workload elevates th…
RadGenome-Chest CT: A Grounded Vision-Language Dataset for Chest CT Analysis
Xiaoman Zhang, Chaoyi Wu, Ziheng Zhao +4
Developing generalist foundation model has recently attracted tremendous attention among researchers in the field of AI for Medicine (AI4Medicine). A pivotal insight in developing…
Knowledge-enhanced Visual-Language Pretraining for Computational Pathology
Xiao Zhou, Xiaoman Zhang, Chaoyi Wu +3
In this paper, we consider the problem of visual representation learning for computational pathology, by exploiting large-scale image-text pairs gathered from public resources, alo…
Towards Building Multilingual Language Model for Medicine
Pengcheng Qiu, Chaoyi Wu, Xiaoman Zhang +5
The development of open-source, multilingual medical language models can benefit a wide, linguistically diverse audience from different regions. To promote this domain, we present…
Large-Vocabulary Segmentation for Medical Images with Text Prompts
Ziheng Zhao, Yao Zhang, Chaoyi Wu +5
This paper aims to build a model that can Segment Anything in 3D medical images, driven by medical terminologies as Text prompts, termed as SAT. Our main contributions are three-fo…
Large-scale Long-tailed Disease Diagnosis on Radiology Images
Qiaoyu Zheng, Weike Zhao, Chaoyi Wu +7
Developing a generalist radiology diagnosis system can greatly enhance clinical diagnostics. In this paper, we introduce RadDiag, a foundational model supporting 2D and 3D inputs a…
Can GPT-4V(ision) Serve Medical Applications? Case Studies on GPT-4V for Multimodal Medical Diagnosis
Chaoyi Wu, Jiayu Lei, Qiaoyu Zheng +8
Driven by the large foundation models, the development of artificial intelligence has witnessed tremendous progress lately, leading to a surge of general interest from the public.…
UniBrain: Universal Brain MRI Diagnosis with Hierarchical Knowledge-enhanced Pre-training
Jiayu Lei, Lisong Dai, Haoyun Jiang +9
Magnetic resonance imaging~(MRI) have played a crucial role in brain disease diagnosis, with which a range of computer-aided artificial intelligence methods have been proposed. How…
Towards Generalist Foundation Model for Radiology by Leveraging Web-scale 2D&3D Medical Data
Chaoyi Wu, Xiaoman Zhang, Ya Zhang +2
In this study, we aim to initiate the development of Radiology Foundation Model, termed as RadFM. We consider the construction of foundational models from three perspectives, namel…
PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering
Xiaoman Zhang, Chaoyi Wu, Ziheng Zhao +4
Medical Visual Question Answering (MedVQA) presents a significant opportunity to enhance diagnostic accuracy and healthcare delivery by leveraging artificial intelligence to interp…
PMC-LLaMA: Towards Building Open-source Language Models for Medicine
Chaoyi Wu, Weixiong Lin, Xiaoman Zhang +3
Recently, Large Language Models (LLMs) have showcased remarkable capabilities in natural language understanding. While demonstrating proficiency in everyday conversations and quest…
PMC-CLIP: Contrastive Language-Image Pre-training using Biomedical Documents
Weixiong Lin, Ziheng Zhao, Xiaoman Zhang +4
Foundation models trained on large-scale dataset gain a recent surge in CV and NLP. In contrast, development in biomedical domain lags far behind due to data scarcity. To address t…