Psychiatry

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

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Machine Learning to Understand the Immune-Inflammatory Pathways in Fibromyalgia.

Fibromyalgia (FM) is a chronic syndrome characterized by widespread musculoskeletal pain, and physic...

Identifying schizophrenia subgroups using clustering and supervised learning.

Schizophrenia has a 1% incidence rate world-wide and those diagnosed present with positive (e.g. hal...

Functional connectivity-based classification of autism and control using SVM-RFECV on rs-fMRI data.

Considering the unsatisfactory classification accuracy of autism due to unsuitable features selected...

Characterizing functional regional homogeneity (ReHo) as a B-SNIP psychosis biomarker using traditional and machine learning approaches.

BACKGROUND: Recently, a biologically-driven psychosis classification (B-SNIP Biotypes) was derived u...

Automated detection of altered mental status in emergency department clinical notes: a deep learning approach.

BACKGROUND: Machine learning has been used extensively in clinical text classification tasks. Deep l...

The risks of risk. Regulating the use of machine learning for psychosis prediction.

Recent advances in Machine Learning (ML) have the potential to revolutionise psychosis prediction an...

Multi-view learning-based data proliferator for boosting classification using highly imbalanced classes.

BACKGROUND: Multi-view data representation learning explores the relationship between the views and ...

Assisted therapeutic system based on reinforcement learning for children with autism.

Assisted therapy is increasingly used in autism spectrum disorders (ASD) for improving social intera...

Can Machine Learning help us in dealing with treatment resistant depression? A review.

BACKGROUND: About one third of patients treated with antidepressant do not show sufficient symptoms ...

Discriminating schizophrenia using recurrent neural network applied on time courses of multi-site FMRI data.

BACKGROUND: Current fMRI-based classification approaches mostly use functional connectivity or spati...

The Future of Digital Psychiatry.

PURPOSE OF REVIEW: Treatments in psychiatry have been rapidly changing over the last century, follow...

Machine learning and big data: Implications for disease modeling and therapeutic discovery in psychiatry.

INTRODUCTION: Machine learning capability holds promise to inform disease models, the discovery and ...

Using street view data and machine learning to assess how perception of neighborhood safety influences urban residents' mental health.

Previous studies have shown that perceptions of neighborhood safety are associated with various ment...

Validation of oxidative stress assay for schizophrenia.

Accumulating evidence implicates oxidative stress in a range of diseases, yet no objective measureme...

Classification of schizophrenia and normal controls using 3D convolutional neural network and outcome visualization.

BACKGROUND: The recent deep learning-based studies on the classification of schizophrenia (SCZ) usin...

Computer- and Robot-Assisted Therapies to Aid Social and Intellectual Functioning of Children with Autism Spectrum Disorder.

BACKGROUND AND OBJECTIVES: Children with autism spectrum disorder (ASD) experience challenges with s...

Detection of major depressive disorder from linear and nonlinear heart rate variability features during mental task protocol.

BACKGROUND: Major depressive disorder (MDD) is one of the leading causes of disability; however, cur...

A difference degree test for comparing brain networks.

Recently, there has been a proliferation of methods investigating functional connectivity as a bioma...

The utility of artificial intelligence in suicide risk prediction and the management of suicidal behaviors.

OBJECTIVE: Suicide is a growing public health concern with a global prevalence of approximately 800,...

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