Psychiatry

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

5,327 articles
Stay Ahead - Weekly Psychiatry research updates
Subscribe
Browse Specialties
Showing 778-798 of 5,327 articles
Reevaluating feature importances in machine learning models for schizophrenia and bipolar disorder: The need for true associations.

Skorobogatov et al. developed supervised machine learning models to predict diagnoses and illness st...

Facial expression analysis using convolutional neural network for drug-naive and chronic schizophrenia.

OBJECTIVE: Facial images have been shown to convey mental conditions as clinical symptoms. This stud...

Enhanced interpretable thyroid disease diagnosis by leveraging synthetic oversampling and machine learning models.

Thyroid illness encompasses a range of disorders affecting the thyroid gland, leading to either hype...

STANet: A Novel Spatio-Temporal Aggregation Network for Depression Classification with Small and Unbalanced FMRI Data.

: Early diagnosis of depression is crucial for effective treatment and suicide prevention. Tradition...

Public Perception on Artificial Intelligence-Driven Mental Health Interventions: Survey Research.

BACKGROUND: Artificial intelligence (AI) has become increasingly important in health care, generatin...

A deep learning approach for automated scoring of the Rey-Osterrieth complex figure.

Memory deficits are a hallmark of many different neurological and psychiatric conditions. The Rey-Os...

Exploring new scientific innovations in combating suicide: a stress detection wristband.

There is a silent pandemic of suicides around the world, with an exponential increase in suicidality...

Machine-Learning Mental-Fatigue-Measuring μm-Thick Elastic Epidermal Electronics (MMMEEE).

Electrophysiological (EP) signals are key biomarkers for monitoring mental fatigue (MF) and general ...

The efficacy of topological properties of functional brain networks in identifying major depressive disorder.

Major Depressive Disorder (MDD) is a common mental disorder characterized by cognitive impairment, a...

Current update on the neurological manifestations of long COVID: more questions than answers.

Since the outbreak of the COVID-19 pandemic, there has been a global surge in patients presenting wi...

BPEN: Brain Posterior Evidential Network for trustworthy brain imaging analysis.

The application of deep learning techniques to analyze brain functional magnetic resonance imaging (...

Disentangling the Genetic Landscape of Peripartum Depression: A Multi-Polygenic Machine Learning Approach on an Italian Sample.

BACKGROUND: The genetic determinants of peripartum depression (PPD) are not fully understood. Using ...

Motivation and socialization during summer predict medical students' success: An artificial intelligence study.

PURPOSE: The latest reform of French medical studies has moved the National Ranking Examination befo...

The relationship between artificial intelligence anxiety and unemployment anxiety among university students.

BackgroundThe idea that people will lose their jobs because of robots with artificial intelligence i...

Multimodal machine learning for language and speech markers identification in mental health.

BACKGROUND: There are numerous papers focusing on diagnosing mental health disorders using unimodal ...

Evolution of Linguistic Markers of Agency, Centrality and Content During Metacognitive Therapy for Psychosis: A Pilot Exploratory Study.

AIM: Metacognitive Reflection and Insight Therapy (MERIT) is a form of person-centred psychotherapy ...

Exploring sensory alterations and repetitive behaviors in children with autism spectrum disorder from the perspective of artificial neural networks.

BACKGROUND: Restrictive repetitive behaviors (RRBs) and sensory processing disorders are core sympto...

Predicting suicidal behavior outcomes: an analysis of key factors and machine learning models.

BACKGROUND: Suicidal behaviors, which may lead to death (suicide) or survival (suicide attempt), are...

A digital phenotyping dataset for impending panic symptoms: a prospective longitudinal study.

This study investigated the utilization of digital phenotypes and machine learning algorithms to pre...

Early diagnostic value of home video-based machine learning in autism spectrum disorder: a meta-analysis.

UNLABELLED: Machine learning (ML) based on remote video has shown ideal diagnostic value in autism s...

Browse Specialties