dgcl-brain-network-construction
CommunityEnd-to-end brain network construction with DGCL.
Data & Analytics#diffusion#fMRI#brain-network-construction#dgcl#graph-contrastive-learning#disease-classification
Authorhiyenwong
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This skill automates end-to-end brain network construction from fMRI data using a diffusion-based brain region-aware module (BRAM) and graph contrastive learning to improve consistency and reduce manual parameter tuning.
Core Features & Use Cases
- End-to-end pipeline: BRAM diffusion localization, initial network construction, graph contrastive learning, and joint loss optimization.
- Disease-focused analysis: supports Alzheimer's and Autism datasets (ADNI, ABIDE) for disease-stage prediction and important connection analysis.
- Efficient, reproducible workflows suitable for research and clinical studies.
Quick Start
Run the DGCL brain network construction workflow on your fMRI dataset to obtain the optimized brain network and key connections.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: dgcl-brain-network-construction Download link: https://github.com/hiyenwong/ai_collection/archive/main.zip#dgcl-brain-network-construction Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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