260 citations · 1.2k across the 75 of their papers we have counts for
9 papers · 1 filter
Agentic AI Enhances Physician Trust in Clinical Decision Making
Zhiling Yan, Zhe Fang, David J King +10
Medical AI has shifted from reasoning to agentic AI, a new paradigm that autonomously invokes external tools during reasoning, rendering intermediate reasoning steps and tool outpu…
Towards a Virtual Neuroscientist: Autonomous Neuroimaging Analysis via Multi-Agent Collaboration
Keqi Han, Songlin Zhao, Yao Su +4
Transforming neuroimaging data into clinically actionable biomarkers is a knowledge-intensive and labor-intensive process. Standardized workflows such as fMRIPrep have improved rob…
Supervised Deep Multimodal Matrix Factorization for Interpretable Brain Network Analysis
Amjad Seyedi, Lifang He, Songlin Zhao +2
Multimodal brain network analysis faces a persistent trade-off between predictive accuracy and interpretability. Deep neural networks achieve high accuracy but behave as black boxe…
Joint Imaging-ROI Representation Learning via Cross-View Contrastive Alignment for Brain Disorder Classification
Wei Liang, Lifang He
Brain imaging classification is commonly approached from two perspectives: modeling the full image volume to capture global anatomical context, or constructing ROI-based graphs to…
Adaptive Clinical-Aware Latent Diffusion for Multimodal Brain Image Generation and Missing Modality Imputation
Rong Zhou, Houliang Zhou, Yao Su +4
Multimodal neuroimaging provides complementary insights for Alzheimer's disease diagnosis, yet clinical datasets frequently suffer from missing modalities. We propose ACADiff, a fr…
Diffusion-Guided Pretraining for Brain Graph Foundation Models
Xinxu Wei, Rong Zhou, Lifang He +1
With the growing interest in foundation models for brain signals, graph-based pretraining has emerged as a promising paradigm for learning transferable representations from connect…
SDE-Driven Spatio-Temporal Hypergraph Neural Networks for Irregular Longitudinal fMRI Connectome Modeling in Alzheimer's Disease
Ruiying Chen, Yutong Wang, Houliang Zhou +3
Longitudinal neuroimaging is essential for modeling disease progression in Alzheimer's disease (AD), yet irregular sampling and missing visits pose substantial challenges for learn…
MedGPT-oss: Training a General-Purpose Vision-Language Model for Biomedicine
Kai Zhang, Zhengqing Yuan, Cheng Peng +10
Biomedical multimodal assistants have the potential to unify radiology, pathology, and clinical-text reasoning, yet a critical deployment gap remains: top-performing systems are ei…
Digital Twin AI: Opportunities and Challenges from Large Language Models to World Models
Rong Zhou, Dongping Chen, Zihan Jia +24
Digital twins, as precise digital representations of physical systems, have evolved from passive simulation tools into intelligent and autonomous entities through the integration o…