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Eeg gcnn contribution #929

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32ea8f0
feat: add EEG-GCNN dataset and neurological disease detection task
Mar 31, 2026
4ce853e
fix: map connectivity_measure to mne_connectivity method names
Apr 1, 2026
c13efd6
feat: add --demo mode to ablation script for synthetic data runs
Apr 1, 2026
35a4aab
Merge branch 'master' into eeg-gcnn-contribution
jburhan Apr 1, 2026
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1 change: 1 addition & 0 deletions docs/api/datasets.rst
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Expand Up @@ -230,6 +230,7 @@ Available Datasets
datasets/pyhealth.datasets.ISRUCDataset
datasets/pyhealth.datasets.MIMICExtractDataset
datasets/pyhealth.datasets.OMOPDataset
datasets/pyhealth.datasets.EEGGCNNDataset
datasets/pyhealth.datasets.DREAMTDataset
datasets/pyhealth.datasets.SHHSDataset
datasets/pyhealth.datasets.SleepEDFDataset
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12 changes: 12 additions & 0 deletions docs/api/datasets/pyhealth.datasets.EEGGCNNDataset.rst
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pyhealth.datasets.EEGGCNNDataset
===================================

Dataset for the EEG-GCNN paper (Wagh & Varatharajah, ML4H @ NeurIPS 2020).
Pools the TUAB normal-subset (patient EEGs) and MPI LEMON (healthy controls).

Paper: https://proceedings.mlr.press/v136/wagh20a.html

.. autoclass:: pyhealth.datasets.EEGGCNNDataset
:members:
:undoc-members:
:show-inheritance:
3 changes: 3 additions & 0 deletions docs/api/tasks.rst
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Expand Up @@ -212,6 +212,9 @@ Available Tasks
COVID-19 CXR Classification <tasks/pyhealth.tasks.COVID19CXRClassification>
DKA Prediction (MIMIC-IV) <tasks/pyhealth.tasks.dka>
Drug Recommendation <tasks/pyhealth.tasks.drug_recommendation>
EEG-GCNN Disease Detection <tasks/pyhealth.tasks.eeg_gcnn_nd_detection>
EEG Abnormal <tasks/pyhealth.tasks.EEG_abnormal>
EEG Events <tasks/pyhealth.tasks.EEG_events>
Length of Stay Prediction <tasks/pyhealth.tasks.length_of_stay_prediction>
Medical Transcriptions Classification <tasks/pyhealth.tasks.MedicalTranscriptionsClassification>
Mortality Prediction (Next Visit) <tasks/pyhealth.tasks.mortality_prediction>
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16 changes: 16 additions & 0 deletions docs/api/tasks/pyhealth.tasks.eeg_gcnn_nd_detection.rst
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pyhealth.tasks.eeg_gcnn_nd_detection
=========================================

Neurological disease detection task from the EEG-GCNN paper (Wagh & Varatharajah, ML4H @ NeurIPS 2020).

Binary classification: patient-normal (TUAB) vs healthy-control (LEMON).

The task extracts PSD band-power features and graph adjacency matrices from EEG recordings,
supporting configurable adjacency types, frequency bands, and connectivity measures for ablation studies.

Paper: https://proceedings.mlr.press/v136/wagh20a.html

.. autoclass:: pyhealth.tasks.eeg_gcnn_nd_detection.EEGGCNNDiseaseDetection
:members:
:undoc-members:
:show-inheritance:
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