AIMC Topic: Depressive Disorder, Major

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Temporal dynamic alterations of regional homogeneity in major depressive disorder: a study integrating machine learning.

Neuroreport
Previous studies have found alterations in the local regional homogeneity of brain activity in individuals diagnosed with major depressive disorder. However, many studies have failed to consider that even during resting states, brain activity is dyna...

Identification of Pyroptosis-Related Molecular Subtypes and Diagnostic Model development in Major Depressive Disorder.

Molecular biotechnology
Major depressive disorder (MDD) is a prevalent psychological disorder associated with inflammation, with complex pathological mechanisms. Pyroptosis has been suggested to contribute to inflammation in central nervous system diseases. Little research,...

Spatiotemporal discoordination of brain spontaneous activity in major depressive disorder.

Journal of affective disorders
BACKGROUND: Major depressive disorder (MDD) is a widespread mental health issue, impacting spatial and temporal aspects of brain activity. The neural mechanisms behind MDD remain unclear. To address this gap, we introduce a novel measure, spatiotempo...

Identifying neuroimaging biomarkers in major depressive disorder using machine learning algorithms and functional near-infrared spectroscopy (fNIRS) during verbal fluency task.

Journal of affective disorders
One of the most prevalent psychiatric disorders is major depressive disorder (MDD), which increases the probability of suicidal ideation or untimely demise. Abnormal frontal hemodynamic changes detected by functional near-infrared spectroscopy (fNIRS...

Multilevel hybrid handcrafted feature extraction based depression recognition method using speech.

Journal of affective disorders
BACKGROUND AND PURPOSE: Diagnosis of depression is based on tests performed by psychiatrists and information provided by patients or their relatives. In the field of machine learning (ML), numerous models have been devised to detect depression automa...

Enhancing Major Depressive Disorder Diagnosis With Dynamic-Static Fusion Graph Neural Networks.

IEEE journal of biomedical and health informatics
Major Depressive Disorder (MDD) is a debilitating, complex mental condition with unclear mechanisms hindering diagnostic progress. Research links MDD to abnormal brain connectivity using functional magnetic resonance imaging (fMRI). Yet, existing fMR...

Artificial intelligence in the detection and treatment of depressive disorders: a narrative review of literature.

International review of psychiatry (Abingdon, England)
Modern psychiatry aims to adopt precision models and promote personalized treatment within mental health care. However, the complexity of factors underpinning mental disorders and the variety of expressions of clinical conditions make this task arduo...

Causes of death in individuals with lifetime major depression: a comprehensive machine learning analysis from a community-based autopsy center.

BMC psychiatry
BACKGROUND: Depression can be associated with increased mortality and morbidity, but no studies have investigated the specific causes of death based on autopsy reports. Autopsy studies can yield valuable and detailed information on pathological ailme...

Detecting depression severity using weighted random forest and oxidative stress biomarkers.

Scientific reports
This study employs machine learning to detect the severity of major depressive disorder (MDD) through binary and multiclass classifications. We compared models that used only biomarkers of oxidative stress with those that incorporate sociodemographic...