AIMC Topic: Depression

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Personality traits as predictors of depression across the lifespan.

Journal of affective disorders
BACKGROUND: Depression is a major public health concern. A barrier for research has been the heterogeneous nature of depression, complicated by the categorical diagnosis of depression which is based on a cluster of symptoms, each with its own etiolog...

Exploring the Use of Socially Assistive Robots Among Socially Isolated Korean American Older Adults.

Journal of applied gerontology : the official journal of the Southern Gerontological Society
This pilot study explored whether a socially assistive robot (SAR) would have positive effects on Korean American immigrant older adults' health behaviors and emotional well-being and whether the older adults would be receptive to the SAR. A total of...

Explainable multimodal prediction of treatment-resistance in patients with depression leveraging brain morphometry and natural language processing.

Psychiatry research
Although 20 % of patients with depression receiving treatment do not achieve remission, predicting treatment-resistant depression (TRD) remains challenging. In this study, we aimed to develop an explainable multimodal prediction model for TRD using s...

Conversational assessment using artificial intelligence is as clinically useful as depression scales and preferred by users.

Journal of affective disorders
BACKGROUND: Depression is prevalent, chronic, and burdensome. Due to limited screening access, depression often remains undiagnosed. Artificial intelligence (AI) models based on spoken responses to interview questions may offer an effective, efficien...

Effectiveness of animal-assisted therapy and pet-robot interventions in reducing depressive symptoms among older adults: A systematic review and meta-analysis.

Complementary therapies in medicine
BACKGROUND: Systematic reviews suggest that animal-assisted therapy (AAT) and pet-robot interventions (PRI) achieve a reduction in mental health variables such as depressive symptoms. However, these systematic reviews include both randomised and non-...

The Three-Lead EEG Sensor: Introducing an EEG-Assisted Depression Diagnosis System Based on Ant Lion Optimization.

IEEE transactions on biomedical circuits and systems
For depression diagnosis, traditional methods such as interviews and clinical scales have been widely leveraged in the past few decades, but they are subjective, time-consuming, and labor-consuming. With the development of affective computing and Art...

Assessing prognosis in depression: comparing perspectives of AI models, mental health professionals and the general public.

Family medicine and community health
BACKGROUND: Artificial intelligence (AI) has rapidly permeated various sectors, including healthcare, highlighting its potential to facilitate mental health assessments. This study explores the underexplored domain of AI's role in evaluating prognosi...

A machine learning model to predict the risk of depression in US adults with obstructive sleep apnea hypopnea syndrome: a cross-sectional study.

Frontiers in public health
OBJECTIVE: Depression is very common and harmful in patients with obstructive sleep apnea hypopnea syndrome (OSAHS). It is necessary to screen OSAHS patients for depression early. However, there are no validated tools to assess the likelihood of depr...

Towards Personalised Mood Prediction and Explanation for Depression from Biophysical Data.

Sensors (Basel, Switzerland)
Digital health applications using Artificial Intelligence (AI) are a promising opportunity to address the widening gap between available resources and mental health needs globally. Increasingly, passively acquired data from wearables are augmented wi...

A Machine Learning Analysis of Big Metabolomics Data for Classifying Depression: Model Development and Validation.

Biological psychiatry
BACKGROUND: Many metabolomics studies of depression have been performed, but these have been limited by their scale. A comprehensive in silico analysis of global metabolite levels in large populations could provide robust insights into the pathologic...