#psychiatric-ai News & Analysis

Comparing Post-Hoc Explainable AI Methods for Interpreting Black-Box EEG Models in Depression Detection

Researchers compared five post-hoc explainability methods for interpreting deep learning models trained to detect Major Depressive Disorder from EEG data. While different attribution approaches showed partially overlapping patterns emphasizing frontal and temporal brain regions, the study reveals methodological assumptions significantly influence interpretability results, cautioning against treating findings as definitive clinical biomarkers.