1 citations · 1 across the 11 of their papers we have counts for
13 papers
DynFS-MoE: Dynamic Functional-Structural Mixture-of-Experts for Post-Traumatic Epilepsy Diagnosis
Jun-En Ding, Spencer Chen, Henry Noren +6
Post-traumatic epilepsy (PTE) is a severe complication of traumatic brain injury (TBI). Yet, early identification remains challenging due to the complex structural and functional a…
NeuroNarrator: A Generalist EEG-to-Text Foundation Model for Clinical Interpretation via Spectro-Spatial Grounding and Temporal State-Space Reasoning
Guoan Wang, Shihao Yang, Jun-en Ding +2
Electroencephalography (EEG) provides a non-invasive window into neural dynamics at high temporal resolution and plays a pivotal role in clinical neuroscience research. Despite thi…
Chain-of-Thought Reasoning with Large Language Models for Clinical Alzheimer's Disease Assessment and Diagnosis
Tongze Zhang, Jun-En Ding, Melik Ozolcer +5
Alzheimer's disease (AD) has become a prevalent neurodegenerative disease worldwide. Traditional diagnosis still relies heavily on medical imaging and clinical assessment by physic…
NeuroWeaver: An Autonomous Evolutionary Agent for Exploring the Programmatic Space of EEG Analysis Pipelines
Guoan Wang, Shihao Yang, Feng Liu
Although foundation models have achieved remarkable success in general domains, applying them to electroencephalography (EEG) analysis is constrained by substantial data requiremen…
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…
Enhancing Multimodal Medical Image Classification using Cross-Graph Modal Contrastive Learning
Jun-En Ding, Chien-Chin Hsu, Chi-Hsiang Chu +2
The classification of medical images is a pivotal aspect of disease diagnosis, often enhanced by deep learning techniques. However, traditional approaches typically focus on unimod…
Spatial Craving Patterns in Marijuana Users: Insights from fMRI Brain Connectivity Analysis with High-Order Graph Attention Neural Networks
Jun-En Ding, Shihao Yang, Anna Zilverstand +3
The excessive consumption of marijuana can induce substantial psychological and social consequences. In this investigation, we propose an elucidative framework termed high-order gr…
Parkinson's Disease Classification Using Contrastive Graph Cross-View Learning with Multimodal Fusion of SPECT Images and Clinical Features
Jun-En Ding, Chien-Chin Hsu, Feng Liu
Parkinson's Disease (PD) affects millions globally, impacting movement. Prior research utilized deep learning for PD prediction, primarily focusing on medical images, neglecting th…