Psychiatry

Depression

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

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Accuracy of Machine Learning in Predicting Post-Stroke Depression: A Systematic Review and Meta-Analysis.

INTRODUCTION: Post-stroke depression is one of the important complications of stroke and affects pat...

Identifying individuals at risk of post-stroke depression: Development and validation of a predictive model.

OBJECTIVES: To identify the factors associated with post-stroke depression (PSD) and develop a machi...

[Construction of recognition models for subthreshold depression based on multiple machine learning algorithms and vocal emotional characteristics].

OBJECTIVES: To construct vocal recognition classification models using 6 machine learning algorithms...

Accuracy of artificial intelligence-based simulation for assessing lung vessels and volume using unenhanced computed tomography.

OBJECTIVES: The advantages of preoperative three-dimensional (3D) image simulations, which require e...

[Prediction of depression symptoms in seniors and analysis of influencing factors based on explainable machine learning].

This study aims to construct a machine learning model to predict depression symptoms in the elderly...

Identifying Preliminary Risk Profiles for Dissociation in 16- to 25-Year-Olds Using Machine Learning.

INTRODUCTION: Dissociation is associated with clinical severity, increased risk of suicide and self-...

Computing 3-Step Theory of Suicide Factor Scores From Veterans Health Administration Clinical Progress Notes.

BACKGROUND: Literature on how to translate information extracted from clinical progress notes into n...

A psychologically interpretable artificial intelligence framework for the screening of loneliness, depression, and anxiety.

Negative emotions such as loneliness, depression, and anxiety (LDA) are prevalent and pose significa...

Personalization variables in digital mental health interventions for depression and anxiety in adolescents and youth: a scoping review.

INTRODUCTION: The impact of personalization on user engagement and adherence in digital mental healt...

Acoustic-based machine learning approaches for depression detection in Chinese university students.

BACKGROUND: Depression is major global public health problems among university students. Currently, ...

Assessing ML classification algorithms and NLP techniques for depression detection: An experimental case study.

CONTEXT AND BACKGROUND: Depression has affected millions of people worldwide and has become one of t...

From the -Factor to Cognitive Content: Detection and Discrimination of Psychopathologies Based on Explainable Artificial Intelligence.

Differentiating psychopathologies is challenging due to shared underlying mechanisms, such as the -...

The Hypothalamic Medial Preoptic Area-Paraventricular Nucleus Circuit Modulates Depressive-Like Behaviors in a Mouse Model of Postpartum Depression.

Estrogen fluctuations have been implicated in various mood disorders, including perimenopausal and p...

Predicting Suicidal Ideation Among Youths With Autism Spectrum Disorder: An Advanced Machine Learning Study.

This study aimed to predict suicidal ideation among youth with autism spectrum disorder (ASD) by app...

Predicting depression severity using machine learning models: Insights from mitochondrial peptides and clinical factors.

Depression presents a significant challenge to global mental health, often intertwined with factors ...

[From AI to polygenic risk scores: which innovations will shape the future of psychiatry?].

BACKGROUND: In recent years, developments have been made in various research domains, from treatment...

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