Psychiatry

EEG-Based Mental Workload Classification Method Based on Hybrid Deep Learning Model Under IoT.

Automatically detecting human mental workload to prevent mental diseases is highly important. With the development of information technology, remote detection of mental workload is expected. The development of artificial intelligence and Internet of Things technology will also enable the identification of mental workload remotely based on human physiological signals. In this article, a method base...

Spectral Graph Neural Network-Based Multi-Atlas Brain Network Fusion for Major Depressive Disorder Diagnosis.

Major Depressive Disorder (MDD) imposes a substantial burden within the healthcare domain, impacting millions of individuals worldwide. Functional Magnetic Resonance Imaging (fMRI) has emerged as a promising tool for the objective diagnosis of MDD, enabling the investigation of functional connectivity patterns in the brain associated with this disorder. However, most existing methods focus on a si...

How can industrial intelligence change the employment structure of the floating population?

As the wave of industrial intelligence (AI) swept, the demographic dividend era in the Chinese labor market continued to decrease. This study aimed to...

Sexual and Gender Minority Status and Suicide Mortality: An Explainable Artificial Intelligence Analysis.

Suicide risk is elevated in lesbian, gay, bisexual, and transgender (LGBT) individuals. Limited data on LGBT status in healthcare systems hinder our ...

Intensive longitudinal assessment following index trauma to predict development of PTSD using machine learning.

There are significant challenges to identifying which individuals require intervention following exposure to trauma, and a need for strategies to iden...

The Contribution of Explainable Machine Learning Algorithms Using ROI-based Brain Surface Morphology Parameters in Distinguishing Early-onset Schizophrenia From Bipolar Disorder.

RATIONALE AND OBJECTIVES: To differentiate early-onset schizophrenia (EOS) from early-onset bipolar disorder (EBD) using surface-based morphometry mea...

Sensing technologies and machine learning methods for emotion recognition in autism: Systematic review.

BACKGROUND: Human Emotion Recognition (HER) has been a popular field of study in the past years. Despite the great progresses made so far, relatively ...

Exploring the Association Between Structural Racism and Mental Health: Geospatial and Machine Learning Analysis.

BACKGROUND: Structural racism produces mental health disparities. While studies have examined the impact of individual factors such as poverty and edu...

Examining how gamers connect with their avatars to assess their anxiety: A novel artificial intelligence approach.

Research has supported that a gamer's attachment to their avatar can offer significant insights about their mental health, including anxiety. To asses...

Emerging Trends of Self-Harm Using Sodium Nitrite in an Online Suicide Community: Observational Study Using Natural Language Processing Analysis.

BACKGROUND: There is growing concern around the use of sodium nitrite (SN) as an emerging means of suicide, particularly among younger people. Given t...

Minicolumn-Based Episodic Memory Model With Spiking Neurons, Dendrites and Delays.

Episodic memory is fundamental to the brain's cognitive function, but how neuronal activity is temporally organized during its encoding and retrieval ...

Artificial Intelligence and the National Violent Death Reporting System: A Rapid Review.

As the awareness on violent deaths from guns, drugs, and suicides emerges as a public health crisis in the United States, attempts to prevent injury a...

Emergency department risk model: timely identification of patients for outpatient care coordination.

OBJECTIVE: Major depressive disorder (MDD) is linked to a 61% increased risk of emergency department (ED) visits and frequent ED usage. Collaborative ...

Exploring post-COVID-19 health effects and features with advanced machine learning techniques.

COVID-19 is an infectious respiratory disease that has had a significant impact, resulting in a range of outcomes including recovery, continued health...

Research on a machine learning-based adaptive and efficient screening model for psychological symptoms of community correctional prisoners.

Community correction institutions in China frequently employ the Symptom Checklist-90 (SCL-90) and the health survey brief (SF-12) as primary tools fo...

Identifying ADHD-Related Abnormal Functional Connectivity with a Graph Convolutional Neural Network.

Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder that is characterized by inattention, hyperactivity, and impul...

Multi-kernel Learning Fusion Algorithm Based on RNN and GRU for ASD Diagnosis and Pathogenic Brain Region Extraction.

Autism spectrum disorder (ASD) is a complex, severe disorder related to brain development. It impairs patient language communication and social behavi...

The health risks of generative AI-based wellness apps.

Artificial intelligence (AI)-enabled chatbots are increasingly being used to help people manage their mental health. Chatbots for mental health and pa...

Multimodal workflows optimally predict response to repetitive transcranial magnetic stimulation in patients with schizophrenia: a multisite machine learning analysis.

The response variability to repetitive transcranial magnetic stimulation (rTMS) challenges the effective use of this treatment option in patients with...

Improving speech depression detection using transfer learning with wav2vec 2.0 in low-resource environments.

Depression, a pervasive global mental disorder, profoundly impacts daily lives. Despite numerous deep learning studies focused on depression detection...