Psychiatry

Multimodal fusion of structural and functional brain imaging in depression using linked independent component analysis.

Previous structural and functional neuroimaging studies have implicated distributed brain regions an...

Generalizability of machine learning for classification of schizophrenia based on resting-state functional MRI data.

Machine learning has increasingly been applied to classification of schizophrenia in neuroimaging re...

The Bot Will See You Now: A History and Review of Interactive Computerized Mental Health Programs.

The goal of automating complex human activities dates to antiquity. The mental health field has also...

A deep learning framework for automatic diagnosis of unipolar depression.

BACKGROUND AND PURPOSE: In recent years, the development of machine learning (ML) frameworks for aut...

Phasic dopamine release identification using convolutional neural network.

Dopamine has a major behavioral impact related to drug dependence, learning and memory functions, as...

A comparison of machine learning algorithms for the surveillance of autism spectrum disorder.

OBJECTIVE: The Centers for Disease Control and Prevention (CDC) coordinates a labor-intensive proces...

EEG-based single-channel authentication systems with optimum electrode placement for different mental activities.

BACKGROUND: Electroencephalogram (EEG) signals of a brain contain a unique pattern for each person a...

Individualized prediction of depressive disorder in the elderly: A multitask deep learning approach.

INTRODUCTION: Depressive disorder is one of the major public health problems among the elderly. An e...

Machine learning discovery of longitudinal patterns of depression and suicidal ideation.

BACKGROUND AND AIM: Depression is often accompanied by thoughts of self-harm, which are a strong pre...

Machine learning and big data analytics in bipolar disorder: A position paper from the International Society for Bipolar Disorders Big Data Task Force.

OBJECTIVES: The International Society for Bipolar Disorders Big Data Task Force assembled leading re...

A Multi-Domain Connectome Convolutional Neural Network for Identifying Schizophrenia From EEG Connectivity Patterns.

OBJECTIVE: We exploit altered patterns in brain functional connectivity as features for automatic di...

Development and validation of multivariable prediction models of remission, recovery, and quality of life outcomes in people with first episode psychosis: a machine learning approach.

BACKGROUND: Outcomes for people with first-episode psychosis are highly heterogeneous. Few reliable ...

PTSD and its dissociative subtype through the lens of the insula: Anterior and posterior insula resting-state functional connectivity and its predictive validity using machine learning.

Individuals with post-traumatic stress disorder (PTSD) typically experience states of reliving and h...

Machine learning in psychiatry- standards and guidelines.

A LightGBM-Based EEG Analysis Method for Driver Mental States Classification.

Fatigue driving can easily lead to road traffic accidents and bring great harm to individuals and fa...

Digital Innovations for Global Mental Health: Opportunities for Data Science, Task Sharing, and Early Intervention.

PURPOSE: Globally, individuals living with mental disorders are more likely to have access to a mobi...

Clustering suicides: A data-driven, exploratory machine learning approach.

Methods of suicide have received considerable attention in suicide research. The common approach to ...

Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol.

BACKGROUND: The screening of digital footprint for clinical purposes relies on the capacity of weara...

Using machine learning to explain the heterogeneity of schizophrenia. Realizing the promise and avoiding the hype.

Despite extensive research and prodigious advances in neuroscience, our comprehension of the nature ...

Machine-learning-based classification between post-traumatic stress disorder and major depressive disorder using P300 features.

BACKGROUND: The development of optimal classification criteria for specific mental disorders which s...

Symptomatology differences of major depression in psychiatric versus general hospitals: A machine learning approach.

BACKGROUND: Symptomatology differences of major depressive disorder (MDD) in psychiatric and general...