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Found 6 papers, 1 papers with code
Biomarker Investigation using Multiple Brain Measures from MRI through XAI in Alzheimer's Disease Classification
The XAI assessment was conducted across 132 brain parcels, extracted from a combination of the Harvard-Oxford and AAL brain atlases, and compared to well-known pathological regions to measure adherence to domain knowledge.
Normative Modeling via Conditional Variational Autoencoder and Adversarial Learning to Identify Brain Dysfunction in Alzheimer's Disease
Normative modeling is an emerging and promising approach to effectively study disorder heterogeneity in individual participants.
Unified Embeddings of Structural and Functional Connectome via a Function-Constrained Structural Graph Variational Auto-Encoder
Graph theoretical analyses have become standard tools in modeling functional and anatomical connectivity in the brain.
Functional2Structural: Cross-Modality Brain Networks Representation Learning
Since brain networks derived from functional and structural MRI describe the brain topology from different perspectives, exploring a representation that combines these cross-modality brain networks is non-trivial.
Structure-Preserving Graph Kernel for Brain Network Classification
This paper presents a novel graph-based kernel learning approach for connectome analysis.
TempoCave: Visualizing Dynamic Connectome Datasets to Support Cognitive Behavioral Therapy
We introduce TempoCave, a novel visualization application for analyzing dynamic brain networks, or connectomes.
Human-Computer Interaction Neurons and Cognition
