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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review
Shihao Yang, Xiying Huang, Danilo Bernardo +10
The development of large-scale artificial intelligence (AI) models is influencing neuroscience research by enabling end-to-end learning from raw brain signals and neural data. In t…
Variational Mixture of Graph Neural Experts for Alzheimer's Disease Recognition across Frequency Bands in EEG Brain Networks
Jun-En Ding, Anna Zilverstand, Shihao Yang +2
Dementia disorders such as Alzheimer's disease (AD) and frontotemporal dementia (FTD) exhibit overlapping electrophysiological signatures in electroencephalography (EEG) that chall…
RPRO: Ranked Preference Reinforcement Optimization for Enhancing Medical QA and Diagnostic Reasoning
Chia-Hsuan Hsu, Jun-En Ding, Hsin-Ling Hsu +5
Medical question answering requires advanced reasoning that integrates domain knowledge with logical inference. However, existing large language models (LLMs) often generate reason…
No Black Boxes: Interpretable and Interactable Predictive Healthcare with Knowledge-Enhanced Agentic Causal Discovery
Xiaoxue Han, Pengfei Hu, Jun-En Ding +3
Deep learning models trained on extensive Electronic Health Records (EHR) data have achieved high accuracy in diagnosis prediction, offering the potential to assist clinicians in d…
Flexible and Explainable Graph Analysis for EEG-based Alzheimer's Disease Classification
Jing Wang, Jun-En Ding, Feng Liu +4
Alzheimer's Disease is a progressive neurological disorder that is one of the most common forms of dementia. It leads to a decline in memory, reasoning ability, and behavior, espec…
NeuroTree: Hierarchical Functional Brain Pathway Decoding for Mental Health Disorders
Jun-En Ding, Dongsheng Luo, Anna Zilverstand +2
Mental disorders are among the most widespread diseases globally. Analyzing functional brain networks through functional magnetic resonance imaging (fMRI) is crucial for understand…