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Biological Psychology|May 15, 2021
Deep learning applied to electroencephalogram data in mental disorders: A systematic reviewMateo de Bardeci, Cheng Teng Ip, Sebastian Olbrich
Schizophrenia Bulletin|October 28, 2025
Autonomic Flexibility and Early Treatment Success: Heart Rate Variability Predicts Remission in First-Episode PsychosisJudith Rohde, Samantha Weber, Mateo de Bardeci, et al.
Pharmacopsychiatry|August 22, 2024
Twenty-Three Years of Declining Lithium Use: Analysis of a Pharmacoepidemiological Dataset from German-Speaking CountriesWaldemar Greil, Mateo de Bardeci, Nadja Nievergelt, et al.
Progress in Neuro-Psychopharmacology & Biological Psychiatry|January 29, 2026
Psilocybin-induced alterations in EEG power, connectivity and network dynamics in healthy subjects: Correlations with subjective experience and implications for therapeutic applicationsCheng-Teng Ip, Sebastian Olbrich, Mateo de Bardeci, et al.
Translational Psychiatry|January 25, 2024
EEG-vigilance regulation is associated with and predicts ketamine response in major depressive disorderCheng-Teng Ip, Mateo de Bardeci, Golo Kronenberg, et al.
Neuropsychobiology|June 27, 2023
Deep Learning in the Identification of Electroencephalogram Sources Associated with Sexual OrientationAnastasios Ziogas, Andreas Mokros, Wolfram Kawohl, et al.
International Journal of Bipolar Disorders|February 13, 2025
Twenty-four years of prescription patterns in bipolar disorder inpatients with vs without lithium: a pharmacoepidemiological analysis of 8,707 cases in German-speaking countriesWaldemar Greil, Mateo de Bardeci, Nadja Nievergelt, et al.
Communications Medicine|March 24, 2026
Deep learning using electroencephalogram (EEG) data for diagnosing and predicting SSRI response in major depressive disorderSebastian Olbrich, Natalia Jaworska, Sara de la Salle, et al.
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