AIMC Topic: Depression

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Automated depression analysis using convolutional neural networks from speech.

Journal of biomedical informatics
To help clinicians to efficiently diagnose the severity of a person's depression, the affective computing community and the artificial intelligence field have shown a growing interest in designing automated systems. The speech features have useful in...

Factors associated with dementia in elderly.

Ciencia & saude coletiva
We analyzed the factors associated with dementia in the elderly attended at a memory outpatient clinic of the University of Southern Santa Catarina (UNISUL). This is a cross-sectional study with data analysis of medical records from January 2013 to A...

Survey of potential receptivity to robotic-assisted exercise coaching in a diverse sample of smokers and nonsmokers.

PloS one
A prior project found that an intensive (12 weeks, thrice weekly sessions) in-person, supervised, exercise coaching intervention was effective for smoking cessation among depressed women smokers. However, the sample was 90% White and of high socioeco...

Predicting suicide attempts in adolescents with longitudinal clinical data and machine learning.

Journal of child psychology and psychiatry, and allied disciplines
BACKGROUND: Adolescents have high rates of nonfatal suicide attempts, but clinically practical risk prediction remains a challenge. Screening can be time consuming to implement at scale, if it is done at all. Computational algorithms may predict suic...

Automated EEG-based screening of depression using deep convolutional neural network.

Computer methods and programs in biomedicine
In recent years, advanced neurocomputing and machine learning techniques have been used for Electroencephalogram (EEG)-based diagnosis of various neurological disorders. In this paper, a novel computer model is presented for EEG-based screening of de...

Thalamocortical dysrhythmia detected by machine learning.

Nature communications
Thalamocortical dysrhythmia (TCD) is a model proposed to explain divergent neurological disorders. It is characterized by a common oscillatory pattern in which resting-state alpha activity is replaced by cross-frequency coupling of low- and high-freq...

A Machine Learning Approach to Identifying Placebo Responders in Late-Life Depression Trials.

The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry
OBJECTIVE: Despite efforts to identify characteristics associated with medication-placebo differences in antidepressant trials, few consistent findings have emerged to guide participant selection in drug development settings and differential therapeu...

Depression and alcohol use disorder at antiretroviral therapy initiation led to disengagement from care in South Africa.

PloS one
We sought to assess mental health at the time of antiretroviral therapy (ART) initiation and subsequent retention in care over a six-month follow-up period. A total of 136 people living with HIV in South Africa were administered surveys measuring dem...

Identifying causal mechanisms in health care interventions using classification tree analysis.

Journal of evaluation in clinical practice
RATIONALE, AIMS, AND OBJECTIVES: Mediation analysis identifies causal pathways by testing the relationships between the treatment, the outcome, and an intermediate variable that mediates the relationship between the treatment and outcome. This paper ...