8 citations · 30 across the 34 of their papers we have counts for
36 papers
EviDx: Evidence-Aware Active Diagnosis with Scaffolded LLM Agents
Lihang Zeng, Shaoting Zhang, Xiaofan Zhang
Clinical diagnosis is an active evidence-seeking process in which clinicians acquire evidence, update competing hypotheses, and decide when the available evidence is sufficient for…
RareLens: Towards End-to-End Rare Disease Care via Aligning Divergent Large Language Model Reasoning
Xi Chen, Hongru Zhou, Shiyu Feng +24
Rare diseases represent one of the most challenging settings for clinical decision-making, where heterogeneous presentations, sparse evidence and limited expertise create persisten…
Reinforcement Learning for Evidence-Seeking Diagnostic Reasoning with Large Language Models
Shengyi Hua, Kangzhe Hu, Conghui He +2
Recent reasoning-centric Large Language Models (LLMs) have made significant strides, yet they predominantly operate on a passive-inference pattern that assumes complete information…
DeVAR: Low-Dose CT Denoising via Visual Autoregressive Modeling
Xizhuo Zhang, Yannian Gu, Zhongzhen Huang +2
Computed tomography (CT) plays a crucial role in medical diagnosis, but minimizing radiation exposure while maintaining image quality remains a critical challenge. Low-dose CT (LDC…
UniPET: a universal network for high-quality PET image denoising across varied dose reduction factors
Zhiwen Yang, Yang Zhou, Haowei Chen +4
Most existing deep learning-based PET image denoising methods assume a fixed and known dose reduction factor (DRF) for low-dose PET images. However, these methods encounter signifi…
Human-AI Co-reasoning for Clinical Diagnosis with Evidence-Integrated Language Agent
Zhongzhen Huang, Yan Ling, Hong Chen +7
We present PULSE, a medical reasoning agent that combines a domain-tuned large language model with scientific literature retrieval to support diagnostic decision-making in complex…
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…
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…
MedMCP-Calc: Benchmarking LLMs for Realistic Medical Calculator Scenarios via MCP Integration
Yakun Zhu, Yutong Huang, Shengqian Qin +3
Medical calculators are fundamental to quantitative, evidence-based clinical practice. However, their real-world use is an adaptive, multi-stage process, requiring proactive EHR da…
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…
Radiologist Copilot: An Agentic Framework Orchestrating Specialized Tools for Reliable Radiology Reporting
Yongrui Yu, Zhongzhen Huang, Linjie Mu +2
In clinical practice, radiology reporting is an essential yet complex, time-intensive, and error-prone task, particularly for 3D medical images. Existing automated approaches based…
Towards Generalist Intelligence in Dentistry: Vision Foundation Models for Oral and Maxillofacial Radiology
Xinrui Huang, Fan Xiao, Dongming He +5
Oral and maxillofacial radiology plays a vital role in dental healthcare, but radiographic image interpretation is limited by a shortage of trained professionals. While AI approach…
Elicit and Enhance: Advancing Multimodal Reasoning in Medical Scenarios
Zhongzhen Huang, Linjie Mu, Yakun Zhu +3
Effective clinical decision-making depends on iterative, multimodal reasoning across diverse sources of evidence. The recent emergence of multimodal reasoning models has significan…
DiagnosisArena: Benchmarking Diagnostic Reasoning for Large Language Models
Yakun Zhu, Zhongzhen Huang, Linjie Mu +6
The emergence of groundbreaking large language models capable of performing complex reasoning tasks holds significant promise for addressing various scientific challenges, includin…
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…
Unifying Multiple Foundation Models for Advanced Computational Pathology
Wenhui Lei, Yusheng Tan, Anqi Li +7
Foundation models have substantially advanced computational pathology by learning transferable visual representations from large histological datasets, yet their performance varies…
MMXU: A Multi-Modal and Multi-X-ray Understanding Dataset for Disease Progression
Linjie Mu, Zhongzhen Huang, Shengqian Qin +3
Large vision-language models (LVLMs) have shown great promise in medical applications, particularly in visual question answering (MedVQA) and diagnosis from medical images. However…
A Synthetic Data-Driven Radiology Foundation Model for Pan-tumor Clinical Diagnosis
Wenhui Lei, Hanyu Chen, Zitian Zhang +13
AI-assisted imaging made substantial advances in tumor diagnosis and management. However, a major barrier to developing robust oncology foundation models is the scarcity of large-s…
O1 Replication Journey -- Part 3: Inference-time Scaling for Medical Reasoning
Zhongzhen Huang, Gui Geng, Shengyi Hua +5
Building upon our previous investigations of O1 replication (Part 1: Journey Learning [Qin et al., 2024] and Part 2: Distillation [Huang et al., 2024]), this work explores the pote…
Unleashing the Potential of Vision-Language Pre-Training for 3D Zero-Shot Lesion Segmentation via Mask-Attribute Alignment
Yankai Jiang, Wenhui Lei, Xiaofan Zhang +1
Recent advancements in medical vision-language pre-training models have driven significant progress in zero-shot disease recognition. However, transferring image-level knowledge to…
MedDiff-FM: A Diffusion-based Foundation Model for Versatile Medical Image Applications
Yongrui Yu, Yannian Gu, Shaoting Zhang +1
Diffusion models have achieved significant success in both natural image and medical image domains, encompassing a wide range of applications. Previous investigations in medical im…
MeNTi: Bridging Medical Calculator and LLM Agent with Nested Tool Calling
Yakun Zhu, Shaohang Wei, Xu Wang +3
Integrating tools into Large Language Models (LLMs) has facilitated the widespread application. Despite this, in specialized downstream task contexts, reliance solely on tools is i…
DeReStainer: H&E to IHC Pathological Image Translation via Decoupled Staining Channels
Linda Wei, Shengyi Hua, Shaoting Zhang +1
Breast cancer is a highly fatal disease among cancers in women, and early detection is crucial for treatment. HER2 status, a valuable diagnostic marker based on Immunohistochemistr…