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Implements the EEG-GCNN paper (Wagh & Varatharajah, ML4H @ NeurIPS 2020) as a PyHealth 2.0 contribution with dataset, task, tests, docs, and ablation study script. New files: - pyhealth/datasets/eeg_gcnn.py — EEGGCNNDataset (TUAB normal + MPI LEMON) - pyhealth/datasets/configs/eeg_gcnn.yaml — YAML config - pyhealth/tasks/eeg_gcnn_nd_detection.py — EEGGCNNDiseaseDetection task (PSD features, spatial/functional/combined adjacency, configurable bands) - tests/test_eeg_gcnn.py — 23 tests using synthetic data - examples/eeg_gcnn_nd_detection_gcn.py — 3 ablation experiments - RST docs for dataset and task Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
"coherence" must be passed as "coh" to spectral_connectivity_epochs. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The ablation script can now run without real TUAB/LEMON data using `--demo`. Generates 40 synthetic patients with reproducible random PSD features and adjacency matrices, runs all 3 experiments through the full GCN training pipeline. Also fixes a bug where roc_auc_score failed on single-column y_prob output from binary classification. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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