AIMC Topic: Bipolar Disorder
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MRI-based deep learning for differentiating between bipolar and major depressive disorders.
Psychiatry research. Neuroimaging
Sep 25, 2024
Mood disorders, particularly bipolar disorder (BD) and major depressive disorder (MDD), manifest changes in brain structure that can be detected using structural magnetic resonance imaging (MRI). Although structural MRI is a promising diagnostic tool...
Enhanced network synchronization connectivity following transcranial direct current stimulation (tDCS) in bipolar depression: Effects on EEG oscillations and deep learning-based predictors of clinical remission.
Journal of affective disorders
Sep 16, 2024
AIM: To investigate oscillatory networks in bipolar depression, effects of a home-based tDCS treatment protocol, and potential predictors of clinical response.
Machine learning-based discrimination of unipolar depression and bipolar disorder with streamlined shortlist in adolescents of different ages.
Computers in biology and medicine
Sep 16, 2024
BACKGROUND: Variations in symptoms and indistinguishable depression episodes of unipolar depression (UD) and bipolar disorder (BD) make the discrimination difficult and time-consuming. For adolescents with high disease prevalence, an efficient diagno...
Machine learning with multiple modalities of brain magnetic resonance imaging data to identify the presence of bipolar disorder.
Journal of affective disorders
Sep 14, 2024
BACKGROUND: Bipolar disorder (BD) is a chronic psychiatric mood disorder that is solely diagnosed based on clinical symptoms. These symptoms often overlap with other psychiatric disorders. Efforts to use machine learning (ML) to create predictive mod...
Immune-based Machine learning Prediction of Diagnosis and Illness State in Schizophrenia and Bipolar Disorder.
Brain, behavior, and immunity
Aug 14, 2024
BACKGROUND: Schizophrenia and bipolar disorder frequently face significant delay in diagnosis, leading to being missed or misdiagnosed in early stages. Both disorders have also been associated with trait and state immune abnormalities. Recent machine...
A Novel Unsupervised Machine Learning Approach to Assess Postural Dynamics in Euthymic Bipolar Disorder.
IEEE journal of biomedical and health informatics
Aug 6, 2024
Bipolar disorder (BD) is a mood disorder with different phases alternating between euthymia, manic or hypomanic episodes, and depressive episodes. While motor abnormalities are commonly seen during depressive or manic episodes, not much attention has...
Unlocking treatment success: predicting atypical antipsychotic continuation in youth with mania.
BMC medical informatics and decision making
Aug 2, 2024
PURPOSE: This study aimed to create and validate robust machine-learning-based prediction models for antipsychotic drug (risperidone) continuation in children and teenagers suffering from mania over one year and to discover potential variables for cl...
Machine learning applied to the prediction of relapse, hospitalization, and suicide in bipolar disorder using neuroimaging and clinical data: A systematic review.
Journal of affective disorders
Jun 21, 2024
BACKGROUND: Bipolar disorder (BD) is associated with increased morbidity/mortality. Adverse outcome prediction might help with the management of patients with BD.
A machine learning approach for differentiating bipolar disorder type II and borderline personality disorder using electroencephalography and cognitive abnormalities.
PloS one
Jun 21, 2024
This study addresses the challenge of differentiating between bipolar disorder II (BD II) and borderline personality disorder (BPD), which is complicated by overlapping symptoms. To overcome this, a multimodal machine learning approach was employed, ...
Exploring the potential of representation and transfer learning for anatomical neuroimaging: Application to psychiatry.
NeuroImage
Jun 6, 2024
The perspective of personalized medicine for brain disorders requires efficient learning models for anatomical neuroimaging-based prediction of clinical conditions. There is now a consensus on the benefit of deep learning (DL) in addressing many medi...
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