6 papers
CURE: A Multimodal Benchmark for Clinical Understanding and Retrieval Evaluation
Yannian Gu, Zhongzhen Huang, Linjie Mu +3
Multimodal large language models (MLLMs) demonstrate considerable potential in clinical diagnostics, a domain that inherently requires synthesizing complex visual and textual data…
CT-Flow: Orchestrating CT Interpretation Workflow with Model Context Protocol Servers
Yannian Gu, Xizhuo Zhang, Linjie Mu +4
Recent advances in Large Vision-Language Models (LVLMs) have shown strong potential for multi-modal radiological reasoning, particularly in tasks like diagnostic visual question an…
EHRWorld: A Patient-Centric Medical World Model for Long-Horizon Clinical Trajectories
Linjie Mu, Zhongzhen Huang, Yannian Gu +3
World models offer a principled framework for simulating future states under interventions, but realizing such models in complex, high-stakes domains like medicine remains challeng…
MedCEG: Reinforcing Verifiable Medical Reasoning with Critical Evidence Graph
Linjie Mu, Yannian Gu, Zhongzhen Huang +3
Large language models with reasoning capabilities have demonstrated impressive performance across a wide range of domains. In clinical applications, a transparent, step-by-step rea…
CP-Env: Evaluating Large Language Models on Clinical Pathways in a Controllable Hospital Environment
Yakun Zhu, Zhongzhen Huang, Qianhan Feng +5
Medical care follows complex clinical pathways that extend beyond isolated physician-patient encounters, emphasizing decision-making and transitions between different stages. Curre…
Interactive Segmentation and Report Generation for CT Images
Yannian Gu, Wenhui Lei, Hanyu Chen +2
Automated CT report generation plays a crucial role in improving diagnostic accuracy and clinical workflow efficiency. However, existing methods lack interpretability and impede pa…