AIMC Topic: Depressive Disorder
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Different prefrontal cortex activity patterns in bipolar and unipolar depression during verbal fluency tasks based on functional near infrared spectroscopy study.
Scientific reports
Jul 1, 2025
This study aimed to investigate the functionality of the prefrontal cortex in patients with unipolar depression (UD) and bipolar depression (BD) using functional near-infrared spectroscopy (fNIRS) during a verbal fluency task (VFT). Additionally, it ...
Machine learning models of depression in middle-aged and older adults with cardiovascular metabolic diseases.
Journal of affective disorders
May 27, 2025
BACKGROUND: The incidence of cardiovascular metabolic diseases (CMD) is increasing, and depression in CMD patients significantly impacts prognosis. Therefore, this study aimed to develop and validate a predictive model for depression in CMD patients ...
Using Digital Phenotyping to Discriminate Unipolar Depression and Bipolar Disorder: Systematic Review.
Journal of medical Internet research
May 23, 2025
BACKGROUND: Differentiating bipolar disorder (BD) from unipolar depression (UD) is essential, as these conditions differ greatly in their progression and treatment approaches. Digital phenotyping, which involves using data from smartphones or other d...
Multimodal depression recognition and analysis: Facial expression and body posture changes via emotional stimuli.
Journal of affective disorders
Apr 3, 2025
BACKGROUND: Clinical studies have shown that facial expressions and body posture in depressed patients differ significantly from those of healthy individuals. Combining relevant behavioral features with artificial intelligence technology can effectiv...
Machine learning-driven development of a stratified CES-D screening system: optimizing depression assessment through adaptive item selection.
BMC psychiatry
Mar 26, 2025
OBJECTIVE: To develop a stratified screening tool through machine learning approaches for the Center for Epidemiologic Studies Depression Scale (CES-D-20) while maintaining diagnostic accuracy, addressing the efficiency limitations in large-scale app...
An interpretable deep-learning approach to detect biomarkers in anxious-depressed symptoms from prefrontal fNIRS signals during an autobiographical memory test.
Asian journal of psychiatry
Mar 22, 2025
BACKGROUND: Individuals with anxious-depressed (AD) symptoms have more severe mood disorders and cognitive impairment than those with non-anxious depression (NAD) symptoms. Therefore, it is important to clarify the underlying neurophysiology of these...
Efficacy and effectiveness of therapist-guided internet versus face-to-face cognitive behavioural therapy for depression via counterfactual inference using naturalistic registers and machine learning in Finland: a retrospective cohort study.
The lancet. Psychiatry
Feb 12, 2025
BACKGROUND: According to meta-analyses of randomised controlled trials (RCTs), therapist-guided internet-delivered cognitive behavioural therapy (iCBT) is as effective a treatment for depression as traditional face-to-face CBT (fCBT), despite its sub...
Auxiliary identification of depression patients using interpretable machine learning models based on heart rate variability: a retrospective study.
BMC psychiatry
Dec 18, 2024
OBJECTIVE: Depression has emerged as a global public health concern with high incidence and disability rates, which are timely imperative to identify and intervene in clinical practice. The objective of this study was to explore the association betwe...
Depression diagnosis: EEG-based cognitive biomarkers and machine learning.
Behavioural brain research
Nov 6, 2024
Depression is a complex mental illness that has significant effects on people as well as society. The traditional techniques for the diagnosis of depression, along with the potential of nascent biomarkers especially EEG-based biomarkers, are studied....
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...
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