Psychiatry

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

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Development of a machine learning-based multivariable prediction model for the naturalistic course of generalized anxiety disorder.

BACKGROUND: Generalized Anxiety Disorder (GAD) is a chronic condition. Enabling the prediction of in...

A machine learning model the prediction of athlete engagement based on cohesion, passion and mental toughness.

Athlete engagement is influenced by several factors, including cohesion, passion and mental toughnes...

Detecting noncredible symptomology in ADHD evaluations using machine learning.

INTRODUCTION: Diagnostic evaluations for attention-deficit/hyperactivity disorder (ADHD) are becomin...

The Use of AI in Mental Health Services to Support Decision-Making: Scoping Review.

BACKGROUND: Recent advancements in artificial intelligence (AI) have changed the care processes in m...

Assessment of glymphatic function and white matter integrity in children with autism using multi-parametric MRI and machine learning.

OBJECTIVES: To assess glymphatic function and white matter integrity in children with autism spectru...

Applications of Large Language Models in the Field of Suicide Prevention: Scoping Review.

BACKGROUND: Prevention of suicide is a global health priority. Approximately 800,000 individuals die...

Deep learning based prediction of depression and anxiety in patients with type 2 diabetes mellitus using regional electronic health records.

BACKGROUND: Depression and anxiety are prevalent mental health conditions among individuals with typ...

The integrating of environmental sustainability assessment by using bipolar complex fuzzy soft Aczel-Alsina aggregation operators with EDAS approach.

The act of responsibly engaging with the world is referred to as environmental sustainability. It en...

Functional Disability and Psychological Impact in Headache Patients: A Comparative Study Using Conventional Statistics and Machine Learning Analysis.

: Recent research has focused on exploring the relationships between various factors associated with...

Identification of depressive symptoms in adolescents using machine learning combining childhood and adolescence features.

BACKGROUND: Depressive symptoms in adolescents can significantly affect their daily lives and pose r...

A comparative machine learning study of schizophrenia biomarkers derived from functional connectivity.

Functional connectivity holds promise as a biomarker of schizophrenia. Yet, the high dimensionality ...

Identifying Neuro-Inflammatory Biomarkers of Generalized Anxiety Disorder from Lymphocyte Subsets Based on Machine Learning Approaches.

INTRODUCTION: Activation of the inflammatory response system is involved in the pathogenesis of gene...

Proximity-based solutions for optimizing autism spectrum disorder treatment: integrating clinical and process data for personalized care.

Autism Spectrum Disorder (ASD) affects millions of individuals worldwide, presenting challenges in s...

Automated karyogram analysis for early detection of genetic and neurodegenerative disorders: a hybrid machine learning approach.

Anomalous chromosomes are the cause of genetic diseases such as cancer, Alzheimer's, Parkinson's, ep...

Development and application of a machine learning-based antenatal depression prediction model.

BACKGROUND: Antenatal depression (AND), occurring during pregnancy, is associated with severe outcom...

Guardian-BERT: Early detection of self-injury and suicidal signs with language technologies in electronic health reports.

Mental health disorders, including non-suicidal self-injury (NSSI) and suicidal behavior, represent ...

From social media to artificial intelligence: improving research on digital harms in youth.

In this Personal View, we critically evaluate the limitations and underlying challenges of existing ...

Classifying Unstructured Text in Electronic Health Records for Mental Health Prediction Models: Large Language Model Evaluation Study.

BACKGROUND: Prediction models have demonstrated a range of applications across medicine, including u...

Machine learning algorithms for predicting PTSD: a systematic review and meta-analysis.

This study aimed to compare and evaluate the prediction accuracy and risk of bias (ROB) of post-trau...

Time series forecasting of bed occupancy in mental health facilities in India using machine learning.

Machine learning models are vital for forecasting and optimizing healthcare parameters, especially i...

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