1 citations · 2 across the 5 of their papers we have counts for
5 papers
R-GenIMA: Integrating Neuroimaging and Genetics with Interpretable Multimodal AI for Alzheimer's Disease Progression
Kun Zhao, Siyuan Dai, Yingying Zhang +9
Early detection of Alzheimer's disease (AD) requires models capable of integrating macro-scale neuroanatomical alterations with micro-scale genetic susceptibility, yet existing mul…
Why Text Prevails: Vision May Undermine Multimodal Medical Decision Making
Siyuan Dai, Lunxiao Li, Kun Zhao +6
With the rapid progress of large language models (LLMs), advanced multimodal large language models (MLLMs) have demonstrated impressive zero-shot capabilities on vision-language ta…
DRE: An Effective Dual-Refined Method for Integrating Small and Large Language Models in Open-Domain Dialogue Evaluation
Kun Zhao, Bohao Yang, Chen Tang +4
Large Language Models (LLMs) excel at many tasks but struggle with ambiguous scenarios where multiple valid responses exist, often yielding unreliable results. Conversely, Small La…
Zeus: Zero-shot LLM Instruction for Union Segmentation in Multimodal Medical Imaging
Siyuan Dai, Kai Ye, Guodong Liu +2
Medical image segmentation has achieved remarkable success through the continuous advancement of UNet-based and Transformer-based foundation backbones. However, clinical diagnosis…
A Heterogeneous Graph Neural Network Fusing Functional and Structural Connectivity for MCI Diagnosis
Feiyu Yin, Yu Lei, Siyuan Dai +4
Brain connectivity alternations associated with brain disorders have been widely reported in resting-state functional imaging (rs-fMRI) and diffusion tensor imaging (DTI). While ma…