AIMC Topic: Depression

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Perceived social support in the daily life of people with Parkinson's disease: a distinct role and potential classifier.

Scientific reports
Motor outcomes in Parkinson's disease (PD) have long been the primary diagnostic criteria and treatment targets. While non-motor outcomes of PD impact daily well-being, they are rarely targeted by interventions or utilized for classification. Despite...

A machine learning-based approach to predict depression in Chinese older adults with subjective cognitive decline: a longitudinal study.

Scientific reports
This study aims to identify depressive risks in elderly individuals with subjective cognitive decline (SCD) and develop a predictive model using machine learning algorithms to enable timely interventions.Data from the 2015 and 2018 waves of the China...

A new framework for mental illnesses diagnosis using wearable devices aided by improved convolutional neural network.

Scientific reports
Stress inherent in the modern world is considered one of the main causes of Mental Health Disorders (MHDs) that spread in every country around the world. These mental and behavioral problems primarily affect the mind and brain that change emotions an...

Deep learning-based detection of depression by fusing auditory, visual and textual clues.

Journal of affective disorders
BACKGROUND: Early detection of depression is crucial for implementing interventions. Deep learning-based computer vision (CV), semantic, and acoustic analysis have enabled the automated analysis of visual and auditory signals.

Multimodal neuroimaging unveils basal forebrain-limbic system circuit dysregulation in cognitive impairment with depression: a pathway to early diagnosis and intervention.

The journal of prevention of Alzheimer's disease
BACKGROUND: Alzheimer's disease (AD) frequently co-occurs with depressive symptoms, exacerbating both cognitive decline and clinical complexity, yet the neural substrates linking this co-occurrence remain poorly understood. We aimed to investigate th...

Efficacy of swarm-based neural networks in automated depression detection.

Scientific reports
As depression becomes a global pandemic, this research paper presents a comprehensive study for depression diagnosis using a custom-crafted deep learning model optimized with various swarm intelligence algorithms. Three different optimization algorit...

Uncertainty aware domain incremental learning for cross domain depression detection.

Scientific reports
Deep learning techniques have demonstrated significant promise for detecting Major Depressive Disorder (MDD) from textual data but they still face limitations in real-world scenarios. Specifically, given the limited data availability, some efforts ha...

Assessing psychological resilience and its influencing factors in the MSM population by machine learning.

Scientific reports
This study assesses the influence of social support, self-esteem, depression, and education on psychological resilience among men who have sex with men (MSM) to inform policy-making. Data were collected from 1,070 MSM via an online survey in Zhejiang...

Multi-kingdom microbiota analysis reveals bacteria-viral interplay in IBS with depression and anxiety.

NPJ biofilms and microbiomes
Irritable Bowel Syndrome (IBS) is a common gastrointestinal disorder frequently accompanied by psychological symptoms. Bacterial microbiota plays a critical role in mediating local and systemic immunity, and alterations in these microbial communities...

Development and validation of a risk prediction model for depression in patients with chronic obstructive pulmonary disease.

BMC psychiatry
BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is a prevalent respiratory condition often accompanied by depression, which exacerbates disease burden and impairs quality of life. Early identification of depression risk in COPD patients rema...