Psychiatry

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

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Deep Factor Learning for Accurate Brain Neuroimaging Data Analysis on Discrimination for Structural MRI and Functional MRI.

Analysis of neuroimaging data (e.g., Magnetic Resonance Imaging, structural and functional MRI) play...

Unraveling the physiological and psychosocial signatures of pain by machine learning.

BACKGROUND: Pain is a complex subjective experience, strongly impacting health and quality of life. ...

Development of an eye-tracking system based on a deep learning model to assess executive function in patients with mental illnesses.

Patients with mental illnesses, particularly psychosis and obsessive‒compulsive disorder (OCD), freq...

Enhancing Major Depressive Disorder Diagnosis With Dynamic-Static Fusion Graph Neural Networks.

Major Depressive Disorder (MDD) is a debilitating, complex mental condition with unclear mechanisms ...

A Novel Unsupervised Machine Learning Approach to Assess Postural Dynamics in Euthymic Bipolar Disorder.

Bipolar disorder (BD) is a mood disorder with different phases alternating between euthymia, manic o...

Enhancing schizophrenia phenotype prediction from genotype data through knowledge-driven deep neural network models.

This article explores deep learning model design, drawing inspiration from the omnigenic model and g...

Machine learning-enabled detection of attention-deficit/hyperactivity disorder with multimodal physiological data: a case-control study.

BACKGROUND: Attention-Deficit/Hyperactivity Disorder (ADHD) is a multifaceted neurodevelopmental psy...

Assessing dimensions of thought disorder with large language models: The tradeoff of accuracy and consistency.

Natural Language Processing (NLP) methods have shown promise for the assessment of formal thought di...

Predicting the Hallucinogenic Potential of Molecules Using Artificial Intelligence.

The development of new drugs addressing serious mental health and other disorders should avoid the p...

Unlocking treatment success: predicting atypical antipsychotic continuation in youth with mania.

PURPOSE: This study aimed to create and validate robust machine-learning-based prediction models for...

Machine Learning Prediction of Autism Spectrum Disorder From a Minimal Set of Medical and Background Information.

IMPORTANCE: Early identification of the likelihood of autism spectrum disorder (ASD) using minimal i...

Can digital leadership transform AI anxiety and attitude in nurses?

BACKGROUND: The lack of artificial intelligence applications in nursing education and the nursing pr...

Improving treatment completion for young adults with substance use disorder: Machine learning-based prediction algorithms.

Substance use disorder (SUD) treatment completion was intertwined with various factors. However, few...

Predicting the severity of mood and neuropsychiatric symptoms from digital biomarkers using wearable physiological data and deep learning.

Neuropsychiatric symptoms (NPS) and mood disorders are common in individuals with mild cognitive imp...

Neural waves and computation in a neural net model II: Data-like structures and the dynamics of episodic memory.

The computational resources of a neuromorphic network model introduced earlier were investigated in ...

Accuracy and transportability of machine learning models for adolescent suicide prediction with longitudinal clinical records.

Machine Learning models trained from real-world data have demonstrated promise in predicting suicide...

The real ethical issues with AI for clinical psychiatry.

This article explores the ethical issues arising from ordinary AI applications currently used in men...

Artificial intelligence in the detection and treatment of depressive disorders: a narrative review of literature.

Modern psychiatry aims to adopt precision models and promote personalized treatment within mental he...

Speech and language patterns in autism: Towards natural language processing as a research and clinical tool.

Speech and language differences have long been described as important characteristics of autism spec...

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