Schizophrenia

Using fMRI and machine learning to predict symptom improvement following cognitive behavioural therapy for psychosis.

Cognitive behavioural therapy for psychosis (CBTp) involves helping patients to understand and refra...

Identifying a neuroanatomical signature of schizophrenia, reproducible across sites and stages, using machine learning with structured sparsity.

OBJECTIVE: Structural MRI (sMRI) increasingly offers insight into abnormalities inherent to schizoph...

Recognition of Schizophrenia with Regularized Support Vector Machine and Sequential Region of Interest Selection using Structural Magnetic Resonance Imaging.

Structural brain abnormalities in schizophrenia have been well characterized with the application of...

A kernel machine method for detecting higher order interactions in multimodal datasets: Application to schizophrenia.

BACKGROUND: Technological advances are enabling us to collect multimodal datasets at an increasing d...

Is It Ethical to Use Prognostic Estimates from Machine Learning to Treat Psychosis?

Machine learning is a method for predicting clinically relevant variables, such as opportunities for...

A rapid LC-MS/MS method for simultaneous determination of quetiapine and duloxetine in rat plasma and its application to pharmacokinetic interaction study.

Combinations of new antidepressants like duloxetine and second-generation antipsychotics like quetia...

Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images.

The human cerebellum plays an essential role in motor control, is involved in cognitive function (i....

Reading the (functional) writing on the (structural) wall: Multimodal fusion of brain structure and function via a deep neural network based translation approach reveals novel impairments in schizophrenia.

This work presents a novel approach to finding linkage/association between multimodal brain imaging ...

Is there a symptomatic distinction between the affective psychoses and schizophrenia? A machine learning approach.

Dubiety exists over whether clinical symptoms of schizophrenia can be distinguished from affective p...

Drug Repositioning for Schizophrenia and Depression/Anxiety Disorders: A Machine Learning Approach Leveraging Expression Data.

Development of new medications is a lengthy and costly process, and drug repositioning might help to...

Quantum-like behavior without quantum physics II. A quantum-like model of neural network dynamics.

In earlier work, we laid out the foundation for explaining the quantum-like behavior of neural syste...

Machine learning improved classification of psychoses using clinical and biological stratification: Update from the bipolar-schizophrenia network for intermediate phenotypes (B-SNIP).

Towards a new classification of stable phase schizophrenia into major and simple neuro-cognitive psychosis: Results of unsupervised machine learning analysis.

RATIONALE: Deficit schizophrenia, as defined by the Schedule for Deficit Syndrome, may represent a d...

Machine learning classification of first-episode schizophrenia spectrum disorders and controls using whole brain white matter fractional anisotropy.

BACKGROUND: Early diagnosis of schizophrenia could improve the outcome of the illness. Unlike classi...

Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI.

BACKGROUND: A lack of a sufficiently large sample at single sites causes poor generalizability in au...

Investigating brain structural patterns in first episode psychosis and schizophrenia using MRI and a machine learning approach.

In this study, we employed the Maximum Uncertainty Linear Discriminant Analysis (MLDA) to investigat...

In Schizophrenia, Depression, Anxiety, and Physiosomatic Symptoms Are Strongly Related to Psychotic Symptoms and Excitation, Impairments in Episodic Memory, and Increased Production of Neurotoxic Tryptophan Catabolites: a Multivariate and Machine Learning Study.

The depression, anxiety and physiosomatic symptoms (DAPS) of schizophrenia are associated with negat...

Music Intervention Leads to Increased Insular Connectivity and Improved Clinical Symptoms in Schizophrenia.

Schizophrenia is a syndrome that is typically accompanied by delusions and hallucinations that might...

The Early Psychosis Screener (EPS): Quantitative validation against the SIPS using machine learning.

Machine learning techniques were used to identify highly informative early psychosis self-report ite...

Prediction of activation patterns preceding hallucinations in patients with schizophrenia using machine learning with structured sparsity.

Despite significant progress in the field, the detection of fMRI signal changes during hallucinatory...

Neuroanatomical heterogeneity of schizophrenia revealed by semi-supervised machine learning methods.

UNLABELLED: Schizophrenia is associated with heterogeneous clinical symptoms and neuroanatomical alt...