Psychiatry

Depression

Latest AI and machine learning research in depression for healthcare professionals.

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Multi-Modal Adaptive Fusion Transformer Network for the Estimation of Depression Level.

Depression is a severe psychological condition that affects millions of people worldwide. As depress...

From everyday life predictions to suicide prevention: Clinical and ethical considerations in suicide predictive analytic tools.

Advances in artificial intelligence and machine learning have fueled growing interest in the applica...

Reproducibility of automated habenula segmentation via deep learning in major depressive disorder and normal controls with 7 Tesla MRI.

The habenula is one of the most important brain regions for investigating the etiology of psychiatri...

A machine learning approach for predicting suicidal thoughts and behaviours among college students.

Suicidal thoughts and behaviours are prevalent among college students. Yet little is known about scr...

Personalized machine learning of depressed mood using wearables.

Depression is a multifaceted illness with large interindividual variability in clinical response to ...

Depression Diagnosis Modeling With Advanced Computational Methods: Frequency-Domain eMVAR and Deep Learning.

Electroencephalogram (EEG)-based automated depression diagnosis systems have been suggested for earl...

Clinical risk prediction models and informative cluster size: Assessing the performance of a suicide risk prediction algorithm.

Clinical visit data are clustered within people, which complicates prediction modeling. Cluster size...

[Machine learning and suicide prevention: is an algorithm the solution?].

Suicide is inherently difficult to predict. Epidemiological research identified many general risk fa...

Spatio-temporal graph convolutional network for diagnosis and treatment response prediction of major depressive disorder from functional connectivity.

The pathophysiology of major depressive disorder (MDD) has been explored to be highly associated wit...

Performance Assessment of Certain Machine Learning Models for Predicting the Major Depressive Disorder among IT Professionals during Pandemic times.

Major depressive disorder (MDD) is the most common mental disorder in the present day as all individ...

Simple action for depression detection: using kinect-recorded human kinematic skeletal data.

BACKGROUND: Depression, a common worldwide mental disorder, which brings huge challenges to family a...

Predicting women with depressive symptoms postpartum with machine learning methods.

Postpartum depression (PPD) is a detrimental health condition that affects 12% of new mothers. Despi...

A direct comparison of theory-driven and machine learning prediction of suicide: A meta-analysis.

Theoretically-driven models of suicide have long guided suicidology; however, an approach employing ...

Predictive modeling of swell-strength of expansive soils using artificial intelligence approaches: ANN, ANFIS and GEP.

This study presents the development of new empirical prediction models to evaluate swell pressure an...

The Prediction of Body Mass Index from Negative Affectivity through Machine Learning: A Confirmatory Study.

This study investigates on the relationship between affect-related psychological variables and Body ...

Applying a bagging ensemble machine learning approach to predict functional outcome of schizophrenia with clinical symptoms and cognitive functions.

It has been suggested that the relationship between cognitive function and functional outcome in sch...

"When they say weed causes depression, but it's your fav antidepressant": Knowledge-aware attention framework for relationship extraction.

With the increasing legalization of medical and recreational use of cannabis, more research is neede...

Machine Learning Assessment of Early Life Factors Predicting Suicide Attempt in Adolescence or Young Adulthood.

IMPORTANCE: Although longitudinal studies have reported associations between early life factors (ie,...

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