Psychiatry

Schizophrenia diagnosis using the GRU-layer's alpha-EEG rhythm's dependability.

Verifying schizophrenia (SZ) can be assisted by deep learning techniques and patterns in brain activity observed in alpha-EEG recordings. The suggested research provides evidence of the reliability of alpha-EEG rhythm in a Gated-Recurrent-Unit-based deep-learning model for investigating SZ. This study suggests Rudiment Densely-Coupled Convolutional Gated Recurrent Unit (RDCGRU) for the various EEG...

An artificial intelligence tool to assess the risk of severe mental distress among college students in terms of demographics, eating habits, lifestyles, and sport habits: an externally validated study using machine learning.

BACKGROUND: Precisely estimating the probability of mental health challenges among college students is pivotal for facilitating timely intervention and preventative measures. However, to date, no specific artificial intelligence (AI) models have been reported to effectively forecast severe mental distress. This study aimed to develop and validate an advanced AI tool for predicting the likelihood o...

Characterizing Autism Spectrum Disorder Through Fusion of Local Cortical Activation and Global Functional Connectivity Using Game-Based Stimuli and a Mobile EEG System.

The deficit in social interaction skills among individuals with autism spectrum disorder (ASD) is strongly influenced by personal experiences and soci...

Hybrid similarity based feature selection and cascade deep maxout fuzzy network for Autism Spectrum Disorder detection using EEG signal.

Autism Spectrum Disorder (ASD) is a neurological disorder that influences a person's comprehension and way of behaving. It is a lifetime disability th...

Effect of a Group-Based Personal Assistive RObot (PARO) Robot Intervention on Cognitive Function, Autonomic Nervous System Function, and Mental Well-being in Older Adults with Mild Dementia: A Randomized Controlled Trial.

OBJECTIVES: Personal Assistive RObot (PARO) interventions have been used to treat agitation and mood symptoms of dementia effectively. However, the ef...

Determinants of adoption of household water treatment in Haiti using two analysis methods: logistic regression and machine learning.

Household water treatment (HWT) is recommended when safe drinking water is limited. To understand determinants of HWT adoption, we conducted a cross-s...

Designing AI for mental health diagnosis: challenges from sub-Saharan African value-laden judgements on mental health disorders.

Recently clinicians have become more reliant on technologies such as artificial intelligence (AI) and machine learning (ML) for effective and accurate...

Machine Learning, Deep Learning, and Data Preprocessing Techniques for Detecting, Predicting, and Monitoring Stress and Stress-Related Mental Disorders: Scoping Review.

BACKGROUND: Mental stress and its consequent mental health disorders (MDs) constitute a significant public health issue. With the advent of machine le...

Self-Administered Interventions Based on Natural Language Processing Models for Reducing Depressive and Anxiety Symptoms: Systematic Review and Meta-Analysis.

BACKGROUND: The introduction of natural language processing (NLP) technologies has significantly enhanced the potential of self-administered intervent...

Effects of track-based stair climbing robot on muscle activity, usability, and psychological anxiety: a preliminary study.

This study investigated the effects of using the LiftCar-150 track-based stair-climbing robot on muscle activity, usability, and psychological anxiety...

Breaking the silence: leveraging social interaction data to identify high-risk suicide users online using network analysis and machine learning.

Suicidal thought and behavior (STB) is highly stigmatized and taboo. Prone to censorship, yet pervasive online, STB risk detection may be improved thr...

Quality and correctness of AI-generated versus human-written abstracts in psychiatric research papers.

This study aimed to assess the ability of an artificial intelligence (AI)-based chatbot to generate abstracts from academic psychiatric articles. We p...

Trajectory on postpartum depression of Chinese women and the risk prediction models: A machine-learning based three-wave follow-up research.

BACKGROUND: Our study delves into postpartum depression (PPD) extending observation up to six months postpartum, addressing the gap in long-term follo...

Spatiotemporal discoordination of brain spontaneous activity in major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is a widespread mental health issue, impacting spatial and temporal aspects of brain activity. The neural ...

Using Data-Driven Algorithms with Large-Scale Plasma Proteomic Data to Discover Novel Biomarkers for Diagnosing Depression.

Given recent technological advances in proteomics, it is now possible to quantify plasma proteomes in large cohorts of patients to screen for biomarke...

Decoding IBS: a machine learning approach to psychological distress and gut-brain interaction.

PURPOSE: Irritable bowel syndrome (IBS) is a diagnosis defined by gastrointestinal (GI) symptoms like abdominal pain and changes associated with defec...

Identifying neuroimaging biomarkers in major depressive disorder using machine learning algorithms and functional near-infrared spectroscopy (fNIRS) during verbal fluency task.

One of the most prevalent psychiatric disorders is major depressive disorder (MDD), which increases the probability of suicidal ideation or untimely d...

Immune-based Machine learning Prediction of Diagnosis and Illness State in Schizophrenia and Bipolar Disorder.

BACKGROUND: Schizophrenia and bipolar disorder frequently face significant delay in diagnosis, leading to being missed or misdiagnosed in early stages...

Identifying COVID-19 survivors living with post-traumatic stress disorder through machine learning on Twitter.

The COVID-19 pandemic has disrupted people's lives and caused significant economic damage around the world, but its impact on people's mental health h...

A Deep Learning-Derived Transdiagnostic Signature Indexing Hypoarousal and Impulse Control: Implications for Treatment Prediction in Psychiatric Disorders.

BACKGROUND: Psychiatric disorders are traditionally classified within diagnostic categories, but this approach has limitations. The Research Domain Cr...