Psychiatry

Schizophrenia

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

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Multivariate classification of schizophrenia and its familial risk based on load-dependent attentional control brain functional connectivity.

Patients with schizophrenia (SCZ), as well as their unaffected siblings (SIB), show functional conne...

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...

Phasic dopamine release identification using convolutional neural network.

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

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...

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 ...

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...

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...

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...

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...

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...

3D-CNN based discrimination of schizophrenia using resting-state fMRI.

MOTIVATION: This study reports a framework to discriminate patients with schizophrenia and normal he...

Machine-learning based brain age estimation in major depression showing no evidence of accelerated aging.

Molecular biological findings indicate that affective disorders are associated with processes akin t...

SynGO: An Evidence-Based, Expert-Curated Knowledge Base for the Synapse.

Synapses are fundamental information-processing units of the brain, and synaptic dysregulation is ce...

Diagnosis of Human Psychological Disorders using Supervised Learning and Nature-Inspired Computing Techniques: A Meta-Analysis.

A psychological disorder is a mutilation state of the body that intervenes the imperative functionin...

Identifying psychosis spectrum disorder from experience sampling data using machine learning approaches.

The ubiquity of smartphones opened up the possibility of widespread use of the Experience Sampling M...

Semantic Face Hallucination: Super-Resolving Very Low-Resolution Face Images with Supplementary Attributes.

Given a tiny face image, existing face hallucination methods aim at super-resolving its high-resolut...

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