Psychiatry

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

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Semantic abnormalities in schizophrenia and bipolar disorder: A natural language processing approach.

INTRODUCTION: The diagnostic boundaries between schizophrenia and bipolar disorder are controversial...

Predicting Antidepressant Treatment Response From Cortical Structure on MRI: A Mega-Analysis From the ENIGMA-MDD Working Group.

Accurately predicting individual antidepressant treatment response could expedite the lengthy trial-...

Diagnosis of Schizophrenia and Its Subtypes Using MRI and Machine Learning.

PURPOSE: The neurobiological heterogeneity present in schizophrenia remains poorly understood. This ...

Unsupervised Dimensionality Reduction Techniques for the Assessment of ASD Biomarkers.

Autism Spectrum Disorder (ASD) encompasses a range of developmental disabilities marked by differenc...

Comparison of six natural language processing approaches to assessing firearm access in Veterans Health Administration electronic health records.

OBJECTIVE: Access to firearms is associated with increased suicide risk. Our aim was to develop a na...

Mini-mental status examination phenotyping for Alzheimer's disease patients using both structured and narrative electronic health record features.

OBJECTIVE: This study aims to automate the prediction of Mini-Mental State Examination (MMSE) scores...

Deconstructing Cognitive Impairment in Psychosis With a Machine Learning Approach.

IMPORTANCE: Cognitive functioning is associated with various factors, such as age, sex, education, a...

Brain-region specific autism prediction from electroencephalogram signals using graph convolution neural network.

BACKGROUND: Brain variations are responsible for developmental impairments, including autism spectru...

[A study on post-traumatic stress disorder classification based on multi-atlas multi-kernel graph convolutional network].

Post-traumatic stress disorder (PTSD) presents with complex and diverse clinical manifestations, mak...

Multi-target neural network model of anxiolytic activity of chemical compounds using correlation convolution of multiple docking energy spectra.

Anxiety disorders are one of the most common mental health pathologies in the world. They require se...

A multimodal vision transformer for interpretable fusion of functional and structural neuroimaging data.

Multimodal neuroimaging is an emerging field that leverages multiple sources of information to diagn...

Healthcare Professionals' Views on the Use of Passive Sensing and Machine Learning Approaches in Secondary Mental Healthcare: A Qualitative Study.

INTRODUCTION: Globally, many people experience mental health difficulties, and the current workforce...

Detection of suicidality from medical text using privacy-preserving large language models.

BACKGROUND: Attempts to use artificial intelligence (AI) in psychiatric disorders show moderate succ...

Predicting Suicides Among US Army Soldiers After Leaving Active Service.

IMPORTANCE: The suicide rate of military servicemembers increases sharply after returning to civilia...

Primary care research on hypertension: A bibliometric analysis using machine-learning.

Hypertension is one of the most important chronic diseases worldwide. Hypertension is a critical con...

Toward molecular diagnosis of major depressive disorder by plasma peptides using a deep learning approach.

Major depressive disorder (MDD) is a severe psychiatric disorder that currently lacks any objective ...

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