Psychiatry

Depression

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

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Constructing prediction models and analyzing factors in suicidal ideation using machine learning, focusing on the older population.

Suicide among the older population is a significant public health concern in South Korea. As the old...

Machine Learning-Based Evaluation of Suicide Risk Assessment in Crisis Counseling Calls.

OBJECTIVE: Counselor assessment of suicide risk is one key component of crisis counseling, and stand...

Identifying Depression Through Machine Learning Analysis of Omics Data: Scoping Review.

BACKGROUND: Depression is one of the most common mental disorders that affects >300 million people w...

Detecting depression severity using weighted random forest and oxidative stress biomarkers.

This study employs machine learning to detect the severity of major depressive disorder (MDD) throug...

Decoding depression: a comprehensive multi-cohort exploration of blood DNA methylation using machine learning and deep learning approaches.

The causes of depression are complex, and the current diagnosis methods rely solely on psychiatric e...

Predicting negative attitudes towards suicide in social media texts: prediction model development and validation study.

BACKGROUND: Implementing machine learning prediction of negative attitudes towards suicide may impro...

Neuroimaging and natural language processing-based classification of suicidal thoughts in major depressive disorder.

Suicide is a growing public health problem around the world. The most important risk factor for suic...

Factors influencing psychological distress among breast cancer survivors using machine learning techniques.

Breast cancer is the most commonly diagnosed cancer among women worldwide. Breast cancer patients ex...

Tai Chi Movement Recognition and Precise Intervention for the Elderly Based on Inertial Measurement Units and Temporal Convolutional Neural Networks.

(1) Background: The objective of this study was to recognize tai chi movements using inertial measur...

Multilayer Perceptron-Based Wearable Exercise-Related Heart Rate Variability Predicts Anxiety and Depression in College Students.

(1) Background: This study aims to investigate the correlation between heart rate variability (HRV) ...

Evaluating generative AI responses to real-world drug-related questions.

Generative Artificial Intelligence (AI) systems such as OpenAI's ChatGPT, capable of an unprecedente...

Predictive modelling of stress, anxiety and depression: A network analysis and machine learning study.

OBJECTIVE: This study assessed predictors of stress, anxiety and depression during the COVID-19 pand...

Machine learning for antidepressant treatment selection in depression.

Finding the right antidepressant for the individual patient with major depressive disorder can be a ...

Development of a differential treatment selection model for depression on consolidated and transformed clinical trial datasets.

Major depressive disorder (MDD) is the leading cause of disability worldwide, yet treatment selectio...

Predicting State-Level Firearm Suicide Rates: A Machine Learning Approach Using Public Policy Data.

INTRODUCTION: Over 40,000 people die by suicide annually in the U.S., and firearms are the most leth...

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