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Depression

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Direct-acting antivirals (DAA) positively affect depression and cognitive function in patients with chronic hepatitis C.

PloS one
The aim of the study was to determine how depression and cognitive dysfunction in patients with chronic hepatitis C virus (HCV) infection are affected by treatment with direct-acting antivirals (DAA). Fifty-two chronic hepatitis C patients underwent ...

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
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...

The interpretable machine learning model for depression associated with heavy metals via EMR mining method.

Scientific reports
Limited research exists on the association between depression and heavy metal exposure. This study aims to develop an interpretable and efficient machine learning (ML) model with robust performance to identify depression linked to heavy metal exposur...

Exploring artificial intelligence (AI) Chatbot usage behaviors and their association with mental health outcomes in Chinese university students.

Journal of affective disorders
Technology dependence has long been a critical public health issue, especially among young people. With the development of AI chatbots, many individuals are integrating these tools into their daily lives. However, we have limited knowledge about the ...

Machine learning-driven development of a stratified CES-D screening system: optimizing depression assessment through adaptive item selection.

BMC psychiatry
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...

Network-based predictive models for artificial intelligence: an interpretable application of machine learning techniques in the assessment of depression in stroke patients.

BMC geriatrics
BACKGROUND: Depression is a common complication after a stroke that may lead to increased disability and decreased quality of life. The objective of this study was to develop and validate an interpretable predictive model to assess the risk of depres...

Utilizing machine learning algorithms for predicting Anxiety-Depression Comorbidity Syndrome in Gastroenterology Inpatients (ADCS-GI).

BMC psychiatry
BACKGROUND: Accurately diagnosing Anxiety-Depression Comorbidity Syndrome in Gastroenterology Inpatients (ADCS-GI) shows significant challenges as traditional diagnostic methods fail to meet expectations due to patient hesitance and non-psychiatric h...

Greenspace and depression incidence in the US-based nationwide Nurses' Health Study II: A deep learning analysis of street-view imagery.

Environment international
BACKGROUND: Greenspace exposure is associated with lower depression risk. However, most studies have measured greenspace exposure using satellite-based vegetation indices, leading to potential exposure misclassification and limited policy relevance. ...

Multimodal depression recognition and analysis: Facial expression and body posture changes via emotional stimuli.

Journal of affective disorders
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...