De la autor
Use 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.
Instalare
npx skills add BioTender-max/awesome-bio-agent-skills --skill ibgnn -a claude-code
Se instalează în .claude/skills/ibgnn/ · 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.
Vrei ca agentul să-ți propună skill-uri în timp ce scrii? Vezi cum folosești skill-urile din IDE.
Verificări de siguranță pe SKILL.md
Niciun avertisment.
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.
- 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
- 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
- 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
- glmBioTender-max/awesome-bio-agent-skillsUse this model doc whenever the user wants to run a classical General Linear Model (GLM) for task-evoked fMRI activation analysis. This is a non-deep-learning model route focused on design matrices, first-level/second-level statistics, and statistical maps.Design★ 206
- neurostormBioTender-max/awesome-bio-agent-skillsUse this skill whenever the user wants to run the NeuroSTORM multi-model fMRI platform: preprocessing, pretraining (MAE or contrastive), fine-tuning, inference, or benchmarking. It covers 8 built-in models — NeuroSTORM, SwiFT, BrainGNN, BrainNetworkTransformer (BNT), LG-GNN, Com-BrainTF, IBGNN, BrainNetCNN — across 3 input modalities (voxel 4D, ROI time series 2D, functional connectivity 2D). Triggers include: 'fMRI', 'NeuroSTORM', 'SwiFT', 'BrainGNN', 'BNT', 'BrainNetCNN', 'LG-GNN', 'Com-BrainTF', 'IBGNN', 'fMRI preprocessing', 'fMRI foundation model', 'ROI time series', 'functional connectivity', 'brain graph', 'HCP', 'ABCD', 'UKB', 'ADHD200', 'COBRE', 'UCLA', 'NSD', 'BOLD5000', 'disease diagnosis from fMRI', 'pretrain fMRI model', 'fine-tune fMRI', or any request involving .nii/.nii.gz fMRI volume files.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
Note și recenzii
—
nicio recenzie
Ai încercat acest skill? Notează-l ca să-i ajuți pe alții. Autentifică-te
Discuție
Intră în discuție. Autentifică-te