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Home/Authors/Nikolina Frid

Nikolina Frid

1 indexed paper

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26

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ML×1AI×1

Frequent co-authors

Antonia Šarčević1×

Research Timeline

2026
Comparing Post-Hoc Explainable AI Methods for Interpreting Black-Box EEG Models in Depression Detection

This study compares multiple post-hoc explainable AI methods (e.g., DeepSHAP, GradCAM) to interpret how deep learning models use EEG data to detect Major Depressive Disorder, finding that while methods partially agree on key brain regions, variability exists due to methodological assumptions.

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Papers

cs.LGcs.AIRecentMay 27, 2026

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

Antonia Šarčević, Nikolina Frid

This study compares multiple post-hoc explainable AI methods (e.g., DeepSHAP, GradCAM) to interpret how deep learning models use EEG data to detect Major Depressive Disorder, finding that while method…

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