5 citations · 7 across the 5 of their papers we have counts for
5 papers
Longitudinal Bayesian Learning of Continuous Disease Position across the Alzheimer's Disease Continuum
Yingying Zhang, Kun Zhao, Guodong Liu +10
Alzheimer's disease (AD) progresses as a continuous biological process, whereas most existing neuroimaging-based artificial intelligence methods remain limited to discrete diagnosi…
Artemis: Anatomy-Resolved inTervention for Eliminating Multimodal NeuroImage confounderS
Siyuan Dai, Yang Du, Kun Zhao +6
Multimodal neuroimaging, integrating functional connectivity from fMRI and structural connectivity from DTI, enables non-invasive analysis of brain networks using graph neural netw…
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…
Exploring EEG and Eye Movement Fusion for Multi-Class Target RSVP-BCI
Xujin Li, Wei Wei, Kun Zhao +4
Rapid Serial Visual Presentation (RSVP)-based Brain-Computer Interfaces (BCIs) facilitate high-throughput target image detection by identifying event-related potentials (ERPs) evok…