AIMC Topic: Depressive Disorder, Major

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Use of machine learning in predicting clinical response to transcranial magnetic stimulation in comorbid posttraumatic stress disorder and major depression: A resting state electroencephalography study.

Journal of affective disorders Mar 30, 2019
BACKGROUND: Repetitive transcranial magnetic stimulation (TMS) is clinically effective for major depressive disorder (MDD) and investigational for other conditions including posttraumatic stress disorder (PTSD). Understanding the mechanisms of TMS ac...
Sensitivity and Specificity Male Middle Aged Depressive Disorder, Major Humans Machine Learning Female Support Vector Machine Predictive Value of Tests Electroencephalography Self Report Comorbidity Prefrontal Cortex Stress Disorders, Post-Traumatic Treatment Outcome Transcranial Magnetic Stimulation Rhode Island
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Relative importance of symptoms, cognition, and other multilevel variables for psychiatric disease classifications by machine learning.

Psychiatry research Mar 29, 2019
This study used machine-learning algorithms to make unbiased estimates of the relative importance of various multilevel data for classifying cases with schizophrenia (n = 60), schizoaffective disorder (n = 19), bipolar disorder (n = 20), unipolar dep...
Male Schizophrenic Psychology Middle Aged Depressive Disorder, Major Humans Parents Bipolar Disorder Machine Learning Cognition Female Schizophrenia Adult Psychotic Disorders
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Evaluating the evidence for biotypes of depression: Methodological replication and extension of.

NeuroImage. Clinical Mar 27, 2019
BACKGROUND: Psychiatric disorders are highly heterogeneous, defined based on symptoms with little connection to potential underlying biological mechanisms. A possible approach to dissect biological heterogeneity is to look for biologically meaningful...
Humans Machine Learning Anxiety Disorders Adult Brain Magnetic Resonance Imaging Male Female Connectome Middle Aged Depressive Disorder, Major
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Classifying major depression patients and healthy controls using EEG, eye tracking and galvanic skin response data.

Journal of affective disorders Mar 20, 2019
OBJECTIVE: Major depression disorder (MDD) is one of the most prevalent mental disorders worldwide. Diagnosing depression in the early stage is crucial to treatment process. However, due to depression's comorbid nature and the subjectivity in diagnos...
Eye Movement Measurements Adult Male Depressive Disorder, Major Case-Control Studies Logistic Models Support Vector Machine Electroencephalography Galvanic Skin Response Machine Learning Algorithms Humans Female Young Adult
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Artificial intelligence based discovery of the association between depression and chronic fatigue syndrome.

Journal of affective disorders Mar 8, 2019
BACKGROUND: Both of the modern medicine and the traditional Chinese medicine classify depressive disorder (DD) and chronic fatigue syndrome (CFS) to one type of disease. Unveiling the association between depressive and the fatigue diseases provides a...
Biomarkers Female Adult Male Humans Principal Component Analysis Artificial Intelligence Least-Squares Analysis Fatigue Syndrome, Chronic Magnetic Resonance Spectroscopy Depressive Disorder Middle Aged Depressive Disorder, Major Gene Expression Profiling Metabolomics
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Low-rank network signatures in the triple network separate schizophrenia and major depressive disorder.

NeuroImage. Clinical Feb 18, 2019
Brain imaging studies have revealed that functional and structural brain connectivity in the so-called triple network (i.e., default mode network (DMN), salience network (SN) and central executive network (CEN)) are consistently altered in schizophre...
Supervised Machine Learning Schizophrenia Nerve Net Schizophrenic Psychology Male Middle Aged Depressive Disorder, Major Magnetic Resonance Imaging Female Humans Young Adult Adult
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Electroconvulsive Therapy Induces Cortical Morphological Alterations in Major Depressive Disorder Revealed with Surface-Based Morphometry Analysis.

International journal of neural systems Feb 8, 2019
Although electroconvulsive therapy (ECT) is one of the most effective treatments for major depressive disorder (MDD), the mechanism underlying the therapeutic efficacy and side effects of ECT remains poorly understood. Here, we investigated alteratio...
Organ Size Cerebral Cortex Electroconvulsive Therapy Humans Female Adult Male Middle Aged Depressive Disorder, Major Support Vector Machine Longitudinal Studies
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Using neuroimaging to predict relapse in stimulant dependence: A comparison of linear and machine learning models.

NeuroImage. Clinical Jan 11, 2019
OBJECTIVE: Relapse rates are consistently high for stimulant user disorders. In order to obtain prognostic information about individuals in treatment, machine learning models have been applied to neuroimaging and clinical data. Yet few efforts have b...
Humans Machine Learning Female Adult Longitudinal Studies Methamphetamine Male Neuroimaging Depressive Disorder, Major Recurrence ROC Curve Logistic Models
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Predicting the naturalistic course of depression from a wide range of clinical, psychological, and biological data: a machine learning approach.

Translational psychiatry Nov 5, 2018
Many variables have been linked to different course trajectories of depression. These findings, however, are based on group comparisons with unknown translational value. This study evaluated the prognostic value of a wide range of clinical, psycholog...
Disease Progression Depressive Disorder, Major Follow-Up Studies Dysthymic Disorder Humans Machine Learning Prognosis Female Adult Male Middle Aged
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Machine learning in major depression: From classification to treatment outcome prediction.

CNS neuroscience & therapeutics Aug 23, 2018
AIMS: Major depression disorder (MDD) is the single greatest cause of disability and morbidity, and affects about 10% of the population worldwide. Currently, there are no clinically useful diagnostic biomarkers that are able to confirm a diagnosis of...
Neural Pathways Animals Humans Depressive Disorder, Major Machine Learning Psychiatric Status Rating Scales Brain Treatment Outcome
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