| title: BrainConnect ASD | |
| emoji: ⚡ | |
| colorFrom: red | |
| colorTo: gray | |
| sdk: gradio | |
| sdk_version: 6.14.0 | |
| python_version: "3.13" | |
| app_file: app.py | |
| pinned: true | |
| license: apache-2.0 | |
| short_description: ASD detection from brain connectivity | |
| tags: | |
| - amd | |
| - amd-hackathon-2026 | |
| - medical-ai | |
| - brain-connectivity | |
| - gradio | |
| # BrainConnect-ASD | |
| Site-invariant Autism Spectrum Disorder classification from resting-state fMRI, built for the AMD Developer Hackathon 2026. | |
| ## Models | |
| | Model | Description | | |
| |---|---| | |
| | [Yatsuiii/brain-connect-gcn](https://huggingface.co/Yatsuiii/brain-connect-gcn) | Adversarial Brain Mode Network — 20-model LOSO GCN ensemble, AUC 0.7298 cross-site | | |
| | [lablab-ai-amd-developer-hackathon/asd-interpreter-merged](https://huggingface.co/lablab-ai-amd-developer-hackathon/asd-interpreter-merged) | Qwen2.5-7B fine-tuned clinical interpreter — generates natural language reports from saliency scores | | |
| ## Pipeline | |
| ``` | |
| fMRI (.1D) → preprocessing → FC matrix → GCN ensemble (20 models) → p(ASD) | |
| ↓ | |
| gradient saliency → Qwen2.5-7B → clinical report | |
| ``` | |
| - **60 total models** trained across 3 atlases (CC200, AAL, Harvard-Oxford) × 20 LOSO folds | |
| - **AMD MI300X** (ROCm 7.0) used for all training and LLM inference | |
| - **~20ms** end-to-end inference per subject (preprocessing + 20-model ensemble) | |
| - **1,102 subjects** · 20 acquisition sites · cross-site evaluation only | |