AIMC Topic: Depressive Disorder, Major

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A depression detection approach leveraging transfer learning with single-channel EEG.

Journal of neural engineering
Major depressive disorder (MDD) is a widespread mental disorder that affects health. Many methods combining electroencephalography (EEG) with machine learning or deep learning have been proposed to objectively distinguish between MDD and healthy indi...

Integrative analysis of signaling and metabolic pathways, immune infiltration patterns, and machine learning-based diagnostic model construction in major depressive disorder.

Scientific reports
Major depressive disorder (MDD) is a multifactorial disorder involving genetic and environmental factors, with unclear pathogenesis. This study aims to explore the pathogenic pathway of MDD and its relationship with immune responses and to discover i...

Machine learning-driven risk prediction and feature identification for major depressive disorder and its progression: an exploratory study based on five years of longitudinal data from the US national health survey.

Journal of affective disorders
BACKGROUND: Major depressive disorder (MDD) presents significant public health challenges due to its increasing prevalence and complex risk factors. This study systematically analyzed data from 2019 to 2023 to explore trends in MDD incidence, symptom...

Semantic signals in self-reference: The detection and prediction of depressive symptoms from the daily diary entries of a sample with major depressive disorder.

Journal of psychopathology and clinical science
Individuals with major depressive disorder (MDD) experience fewer positive and more negative emotions and use fewer positive words to describe themselves. Natural language processing techniques have been used to predict depression, with pronoun and e...

Prediction of remission of pharmacologically treated psychotic depression: A machine learning approach.

Journal of affective disorders
BACKGROUND: The combination of antidepressant and antipsychotic medication is an effective treatment for major depressive disorder with psychotic features ('psychotic depression'). The present study aims to identify sociodemographic and clinical pred...

Gene age gap estimate (GAGE) for major depressive disorder: A penalized biological age model using gene expression.

Neurobiology of aging
Recent associations between Major Depressive Disorder (MDD) and measures of premature aging suggest accelerated biological aging as a potential biomarker for MDD susceptibility or MDD as a risk factor for age-related diseases. Residuals or "gaps" bet...

Multivariate Classification of Adolescent Major Depressive Disorder Using Whole-brain Functional Connectivity.

Academic radiology
RATIONALE AND OBJECTIVES: Adolescent major depressive disorder (MDD) is a serious mental health condition that has been linked to abnormal functional connectivity (FC) patterns within the brain. However, whether FC could be used as a potential biomar...

Altered resting-state brain activity in patients with major depression disorder and bipolar disorder: A regional homogeneity analysis.

Journal of affective disorders
BACKGROUND: Major Depressive Disorder (MDD) and Bipolar Disorder (BD) exhibit overlapping depressive symptoms, complicating their differentiation in clinical practice. Traditional neuroimaging studies have focused on specific regions of interest, but...

A machine learning approach to predict treatment efficacy and adverse effects in major depression using CYP2C19 and clinical-environmental predictors.

Psychiatric genetics
BACKGROUND: Major depressive disorder (MDD) is among the leading causes of disability worldwide and treatment efficacy is variable across patients. Polymorphisms in cytochrome P450 2C19 (CYP2C19) play a role in response and side effects to medication...

Circadian rhythm modulation in heart rate variability as potential biomarkers for major depressive disorder: A machine learning approach.

Journal of psychiatric research
Major depressive disorder (MDD) is associated with reduced heart rate variability (HRV), but its link to circadian rhythm modulation (CRM) of HRV is unclear. Given that depression disrupts circadian rhythms, assessing HRV fluctuations may better capt...