23 papers
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…