Psychiatry

Mental Health Applications of Generative AI and Large Language Modeling in the United States.

(1) Background: Artificial intelligence (AI) has flourished in recent years. More specifically, generative AI has had broad applications in many disciplines. While mental illness is on the rise, AI has proven valuable in aiding the diagnosis and treatment of mental disorders. However, there is little to no research about precisely how much interest there is in AI technology. (2) Methods: We perfor...

A Novel Implementation of a Social Robot for Sustainable Human Engagement in Homecare Services for Ageing Populations.

This research addresses the rapid aging phenomenon prevalent in Asian societies, which has led to a significant increase in elderly individuals relocating to nursing homes due to health-related issues. This trend has resulted in social isolation and loneliness among the elderly, contributing to physical and mental ailments such as hypertension and cardiovascular diseases, as highlighted by the Wor...

Lung Adenocarcinoma Systems Biomarker and Drug Candidates Identified by Machine Learning, Gene Expression Data, and Integrative Bioinformatics Pipeline.

Lung adenocarcinoma (LUAD) is a significant planetary health challenge with its high morbidity and mortality rate, not to mention the marked interindi...

Contributions of brain regions to machine learning-based classifications of attention deficit hyperactivity disorder (ADHD) utilizing EEG signals.

OBJECTIVE: The study presented focuses on the creation of a machine learning (ML) model that uses electrophysiological (EEG) data to identify kids wit...

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 improve health outcomes. However, in previous studies, ...

RevGraphVAMP: A protein molecular simulation analysis model combining graph convolutional neural networks and physical constraints.

Molecular dynamics simulation is a crucial research domain within the life sciences, focusing on comprehending the mechanisms of biomolecular interact...

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 suicide is underlying psychiatric illness, especially ...

Screening of Secretory Proteins Linking Major Depressive Disorder with Heart Failure Based on Comprehensive Bioinformatics Analysis and Machine Learning.

BACKGROUND: Major depressive disorder (MDD) plays a crucial role in the occurrence of heart failure (HF). This investigation was undertaken to explore...

Using Human Resources Data to Predict Turnover of Community Mental Health Employees: Prediction and Interpretation of Machine Learning Methods.

This study used machine learning (ML) to predict mental health employees' turnover in the following 12 months using human resources data in a communit...

Deep learning for schizophrenia classification based on natural language processing-A pilot study.

An integrated ergonomic risk assessment framework based on fuzzy logic and IVSF-AHP for optimising ergonomic risks in a mixed-model assembly line.

This study proposes a systematic approach to address ergonomic factors, including physical, environmental and psychosocial aspects, in solving assembl...

Predicting long-term sleep deprivation using wearable sensors and health surveys.

Sufficient sleep is essential for individual well-being. Inadequate sleep has been shown to have significant negative impacts on our attention, cognit...

Power spectral density-based resting-state EEG classification of first-episode psychosis.

Historically, the analysis of stimulus-dependent time-frequency patterns has been the cornerstone of most electroencephalography (EEG) studies. The ab...

The Role of Humanization and Robustness of Large Language Models in Conversational Artificial Intelligence for Individuals With Depression: A Critical Analysis.

Large language model (LLM)-powered services are gaining popularity in various applications due to their exceptional performance in many tasks, such as...

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 experience significant distress relating to their di...

Identifying subgroups of urge suppression in Obsessive-Compulsive Disorder using machine learning.

Obsessive-compulsive disorder (OCD) is phenomenologically heterogeneous. While predominant models suggest fear and harm prevention drive compulsions, ...

Wavelet Transform, Reconstructed Phase Space, and Deep Learning Neural Networks for EEG-Based Schizophrenia Detection.

This study proposes an innovative expert system that uses exclusively EEG signals to diagnose schizophrenia in its early stages. For diagnosing psychi...

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) during exercise and recovery periods and the level...

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 measurement units (IMUs) and temporal convolutional neur...

Insights Derived From Text-Based Digital Media, in Relation to Mental Health and Suicide Prevention, Using Data Analysis and Machine Learning: Systematic Review.

BACKGROUND: Text-based digital media platforms have revolutionized communication and information sharing, providing valuable access to knowledge and u...