Psychiatry

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

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A peripheral inflammatory signature discriminates bipolar from unipolar depression: A machine learning approach.

BACKGROUND: Mood disorders (major depressive disorder, MDD, and bipolar disorder, BD) are considered...

Gut microbiome-mediated epigenetic regulation of brain disorder and application of machine learning for multi-omics data analysis.

The gut-brain axis (GBA) is a biochemical link that connects the central nervous system (CNS) and en...

BrainNET: Inference of Brain Network Topology Using Machine Learning.

To develop a new functional magnetic resonance image (fMRI) network inference method, BrainNET, tha...

Deep neural networks detect suicide risk from textual facebook posts.

Detection of suicide risk is a highly prioritized, yet complicated task. Five decades of research ha...

Identifying and validating subtypes within major psychiatric disorders based on frontal-posterior functional imbalance via deep learning.

Converging evidence increasingly implicates shared etiologic and pathophysiological characteristics ...

Can machine learning be useful as a screening tool for depression in primary care?

Depression is a widespread disease with a high economic burden and a complex pathophysiology disease...

[Big Data, AI and Machine Learning for Precision Psychiatry: How are they changing the clinical practice?].

Currently, we are witnessing an increasing interest in predictive models and personalized diagnosis ...

Inner speech.

Inner speech travels under many aliases: the inner voice, verbal thought, thinking in words, interna...

Optimal robot for intervention for individuals with autism spectrum disorders.

With recent rapid advances in technology, human-like robots have begun functioning in a variety of w...

Multi-dimensional predictions of psychotic symptoms via machine learning.

The diagnostic criteria for schizophrenia comprise a diverse range of heterogeneous symptoms. As a r...

Predicting Early Warning Signs of Psychotic Relapse From Passive Sensing Data: An Approach Using Encoder-Decoder Neural Networks.

BACKGROUND: Schizophrenia spectrum disorders (SSDs) are chronic conditions, but the severity of symp...

A scoping review of machine learning in psychotherapy research.

Machine learning (ML) offers robust statistical and probabilistic techniques that can help to make s...

Precision psychiatry in clinical practice.

The treatment of depression represents a major challenge for healthcare systems and choosing among t...

The DREAM Dataset: Supporting a data-driven study of autism spectrum disorder and robot enhanced therapy.

We present a dataset of behavioral data recorded from 61 children diagnosed with Autism Spectrum Dis...

Using de-identified electronic health records to research mental health supported housing services: A feasibility study.

BACKGROUND: Mental health supported housing services are a key component in the rehabilitation of pe...

Identifying resting-state effective connectivity abnormalities in drug-naïve major depressive disorder diagnosis via graph convolutional networks.

Major depressive disorder (MDD) is a leading cause of disability; its symptoms interfere with social...

Disrupted rich-club network organization and individualized identification of patients with major depressive disorder.

BACKGROUND: Altered structural and functional brain networks have been extensively studied in major ...

Artificial Intelligence and Suicide Prevention: A Systematic Review of Machine Learning Investigations.

Suicide is a leading cause of death that defies prediction and challenges prevention efforts worldwi...

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