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AI Predicts Antidepressant Treatment Response with 97% Accuracy
['Alexander Perkins']
European Medical Journal
EEG and AI to Analyse Antidepressant Treatment ResponseDepression is a highly heterogeneous condition, with up to one-third of patients failing to respond adequately to first-line SSRI therapy.
The best-performing EEG SSRI treatment response model was an SVM-based approach using 12-second EEG windows, which achieved 96.83% accuracy.
Neurophysiological Signatures of Antidepressant ResponseBeyond prediction, the analysis revealed distinct neurophysiological patterns associated with SSRI response.
Implications and LimitationsThe authors concluded that Beta2 oscillations and long-range connectivity may serve as reliable biomarkers for SSRI treatment response.
Neurophysiological mechanisms and predictive modeling of SSRI treatment response in depression disorder based on multidimensional EEG features.