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Thomas Stamm

Showing results (81-90 of 112) with videos related to

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Neuroscience Applied|July 14, 2025
Lithium treatment for affective disorders: Exploring the potential of salivary therapeutic monitoringMaja P Völker, Lea Sirignano, Helene Dukal, et al.
International Journal of Bipolar Disorders|May 9, 2017
Long-term lithium treatment in bipolar disorder: effects on glomerular filtration rate and other metabolic parametersLeonardo Tondo, Maria Abramowicz, Martin Alda, et al.
Journal of Affective Disorders|February 18, 2026
Contribution of depressive symptom load on prediction of transition to bipolar disorders: Results from the prospective-longitudinal multi-method Early-BipoLife studyThore Petersen, Julia Martini, Michael Bauer, et al.
European Neuropsychopharmacology : the Journal of the European College of Neuropsychopharmacology|November 1, 2023
Young people at risk for developing bipolar disorder: Two-year findings from the multicenter prospective, naturalistic Early-BipoLife studyJulia Martini, Kyra Luisa Bröckel, Karolina Leopold, et al.
International Journal of Bipolar Disorders|December 30, 2025
Creativity and transition to bipolar disorder: a prospective analysis from the early-bipolife studyElisabeth Michaelis, Michael Bauer, Andreas Bechdolf, et al.
Psychological Medicine|May 22, 2023
Prediction of estimated risk for bipolar disorder using machine learning and structural MRI featuresPavol Mikolas, Michael Marxen, Philipp Riedel, et al.
Translational Psychiatry|September 21, 2021
Individuals at increased risk for development of bipolar disorder display structural alterations similar to people with manifest diseasePavol Mikolas, Kyra Bröckel, Christoph Vogelbacher, et al.
Brain Sciences|June 28, 2023
Machine Learning Prediction of Estimated Risk for Bipolar Disorders Using Hippocampal Subfield and Amygdala Nuclei VolumesFabian Huth, Leonardo Tozzi, Michael Marxen, et al.
Psychological Medicine|May 27, 2024
Larger putamen in individuals at risk and with manifest bipolar disorderFlorian Thomas-Odenthal, Frederike Stein, Christoph Vogelbacher, et al.
JMIR Mental Health|June 22, 2026
Functional Outcome Prediction in Young Adults With Mental Health Symptoms Using Machine Learning and Large Language Models: Longitudinal Observational StudyPavol Mikolas, Fabian Huth, Kyra Bröckel-Bundt, et al.
Pageof 12

Showing results (81-90 of 112) with videos related to

Sort By:
Pageof 12
Neuroscience Applied|July 14, 2025
Lithium treatment for affective disorders: Exploring the potential of salivary therapeutic monitoringMaja P Völker, Lea Sirignano, Helene Dukal, et al.
International Journal of Bipolar Disorders|May 9, 2017
Long-term lithium treatment in bipolar disorder: effects on glomerular filtration rate and other metabolic parametersLeonardo Tondo, Maria Abramowicz, Martin Alda, et al.
Journal of Affective Disorders|February 18, 2026
Contribution of depressive symptom load on prediction of transition to bipolar disorders: Results from the prospective-longitudinal multi-method Early-BipoLife studyThore Petersen, Julia Martini, Michael Bauer, et al.
European Neuropsychopharmacology : the Journal of the European College of Neuropsychopharmacology|November 1, 2023
Young people at risk for developing bipolar disorder: Two-year findings from the multicenter prospective, naturalistic Early-BipoLife studyJulia Martini, Kyra Luisa Bröckel, Karolina Leopold, et al.
International Journal of Bipolar Disorders|December 30, 2025
Creativity and transition to bipolar disorder: a prospective analysis from the early-bipolife studyElisabeth Michaelis, Michael Bauer, Andreas Bechdolf, et al.
Psychological Medicine|May 22, 2023
Prediction of estimated risk for bipolar disorder using machine learning and structural MRI featuresPavol Mikolas, Michael Marxen, Philipp Riedel, et al.
Translational Psychiatry|September 21, 2021
Individuals at increased risk for development of bipolar disorder display structural alterations similar to people with manifest diseasePavol Mikolas, Kyra Bröckel, Christoph Vogelbacher, et al.
Brain Sciences|June 28, 2023
Machine Learning Prediction of Estimated Risk for Bipolar Disorders Using Hippocampal Subfield and Amygdala Nuclei VolumesFabian Huth, Leonardo Tozzi, Michael Marxen, et al.
Psychological Medicine|May 27, 2024
Larger putamen in individuals at risk and with manifest bipolar disorderFlorian Thomas-Odenthal, Frederike Stein, Christoph Vogelbacher, et al.
JMIR Mental Health|June 22, 2026
Functional Outcome Prediction in Young Adults With Mental Health Symptoms Using Machine Learning and Large Language Models: Longitudinal Observational StudyPavol Mikolas, Fabian Huth, Kyra Bröckel-Bundt, et al.
Pageof 12