combraintf
De la autor
Use this model doc whenever the user wants to run Com-BrainTF (Community-aware Brain Transformer) for fMRI phenotype prediction. Com-BrainTF uses dense FC matrices with a two-level Transformer (per-community local + global) and DEC pooling. NeuroClaw auto-derives community partitions from atlas naming conventions (Yeo 7-net for Schaefer, lobe-based for AAL).
Instalare
npx skills add BioTender-max/awesome-bio-agent-skills --skill combraintf -a claude-code
Se instalează în .claude/skills/combraintf/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Fără descărcare: licența acestui skill (Personalizată sau neclară) nu ne permite să-i redistribuim fișierele. Comenzile de instalare le iau direct de pe GitHub.
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Verificări de siguranță pe SKILL.md
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De ce 74
aiqbench calculează scorul de încredere din semnale publice. Nu este un audit de securitate, așa că citește un skill înainte să-l instalezi.
Skill-uri similare
Cele mai apropiate de acesta prin ce fac și când sunt folosite.
- bntBioTender-max/awesome-bio-agent-skillsUse this model doc whenever the user wants to run BrainNetworkTransformer for fMRI phenotype prediction, including data loading, training, and evaluation. BNT uses dense FC matrices (no PyG dependency) with DEC pooling + interpretable transformer encoder.Altele★ 206
- lggnnBioTender-max/awesome-bio-agent-skillsUse this model doc whenever the user wants to run LG-GNN (Local-to-Global GNN) for fMRI phenotype prediction. LG-GNN is a PyG-based GNN with SABP (Self-Attention Brain Pooling) and mutual-information regularization. NeuroClaw adapts the original population-graph version to single-subject brain graphs.Altele★ 206
- braingnnBioTender-max/awesome-bio-agent-skillsUse this model doc whenever the user wants to run BrainGNN for fMRI phenotype prediction, including graph construction, training, and evaluation. This document focuses on model-level usage and delegates upstream preprocessing to fmri-skill (and optionally hcpya-skill for HCP data).Altele★ 206
- fm_appBioTender-max/awesome-bio-agent-skillsUse this model doc whenever the user wants to run FM-APP for phenotype prediction using fMRI ROI features and optional sMRI features. This document provides model-level usage and delegates preprocessing to fmri-skill and smri-skill.Altele★ 206
- smri-skillBioTender-max/awesome-bio-agent-skillsUse this skill whenever the user wants to process structural MRI (sMRI) such as T1w/T2w/FLAIR for brain extraction, bias correction, tissue segmentation (GM/WM/CSF), registration to MNI, cortical/subcortical parcellation, cortical thickness/volumetry (FreeSurfer), HCP-style structural preprocessing, WMH lesion segmentation (FLAIR+T1), ROI-wise feature extraction, or converting results back to DICOM. This is the NeuroClaw modality-layer interface: it plans WHAT to do and delegates execution to tool skills.Design★ 206
- ibgnnBioTender-max/awesome-bio-agent-skillsUse this model doc whenever the user wants to run IBGNN (Interpretable Brain Graph Neural Network) for fMRI phenotype prediction. IBGNN is a PyG-based GNN with a learnable MLP message function over [x_i, x_j, edge_attr], designed for connectome-based brain disorder analysis with post-hoc edge-mask explainer support.Altele★ 206
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