8 citations · 13 across the 10 of their papers we have counts for
12 papers
From Papers to Mechanisms: An Evidence-Grounded Knowledge Substrate for Scientific Language Models
Qiuhui Chen, Yibo Liu, Tao Dai +3
Scientific language models often access literature through untyped text chunks, which fragment the functional and evidential structure required for mechanism-rich questions. We int…
PathAnchor: Path-Structured Evidence for Scientific Agents
Qiuhui Chen, Jiafan Lu, Shuaimin Tang +5
Scientific agents can retrieve relevant passages yet still lose functional order, mix evidence across sources, or state conclusions that exceed the retrieved record. We introduce P…
AT-Attn: Temporal-Aware Cross-Attention for Longitudinal Multimodal Alzheimer's Disease Diagnosis
Xinyue Du, Yibo Liu, Zhenglei Zhou +3
In longitudinal Alzheimer's disease (AD) diagnosis support, clinical and imaging information is often collected at irregular visits. Integrating these multimodal observations may i…
ZSG-IAD: A Multimodal Framework for Zero-Shot Grounded Industrial Anomaly Detection
Qiuhui Chen, Jiaxiang Song, Shuai Tan +1
Deep learning-based industrial anomaly detectors often behave as black boxes, making it hard to justify decisions with physically meaningful defect evidence. We propose ZSG-IAD, a…
AD-Reasoning: Multimodal Guideline-Guided Reasoning for Alzheimer's Disease Diagnosis
Qiuhui Chen, Yushan Deng, Xuancheng Yao +1
Alzheimer's disease (AD) diagnosis requires integrating neuroimaging with heterogeneous clinical evidence and reasoning under established criteria, yet most multimodal models remai…
EMAD: Evidence-Centric Grounded Multimodal Diagnosis for Alzheimer's Disease
Qiuhui Chen, Xuancheng Yao, Zhenglei Zhou +2
Deep learning models for medical image analysis often act as black boxes, seldom aligning with clinical guidelines or explicitly linking decisions to supporting evidence. This is e…
Enhancing 3D Medical Image Understanding with Pretraining Aided by 2D Multimodal Large Language Models
Qiuhui Chen, Xuancheng Yao, Huping Ye +1
Understanding 3D medical image volumes is critical in the medical field, yet existing 3D medical convolution and transformer-based self-supervised learning (SSL) methods often lack…
HoloDx: Knowledge- and Data-Driven Multimodal Diagnosis of Alzheimer's Disease
Qiuhui Chen, Jintao Wang, Gang Wang +1
Accurate diagnosis of Alzheimer's disease (AD) requires effectively integrating multimodal data and clinical expertise. However, existing methods often struggle to fully utilize mu…
Med3DInsight: Enhancing 3D Medical Image Understanding with 2D Multi-Modal Large Language Models
Qiuhui Chen, Huping Ye, Yi Hong
Understanding 3D medical image volumes is a critical task in the medical domain. However, existing 3D convolution and transformer-based methods have limited semantic understanding…
AliFuse: Aligning and Fusing Multi-modal Medical Data for Computer-Aided Diagnosis
Qiuhui Chen, Yi Hong
Medical data collected for diagnostic decisions are typically multimodal, providing comprehensive information on a subject. While computer-aided diagnosis systems can benefit from…
Volumetric Medical Image Segmentation via Scribble Annotations and Shape Priors
Qiuhui Chen, Haiying Lyu, Xinyue Hu +2
Recently, weakly-supervised image segmentation using weak annotations like scribbles has gained great attention in computer vision and medical image analysis, since such annotation…
MedBLIP: Bootstrapping Language-Image Pre-training from 3D Medical Images and Texts
Qiuhui Chen, Xinyue Hu, Zirui Wang +1
Vision-language pre-training (VLP) models have been demonstrated to be effective in many computer vision applications. In this paper, we consider developing a VLP model in the medi…