Psychiatry

Schizophrenia

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

1,907 articles
Stay Ahead - Weekly Schizophrenia research updates
Subscribe
Browse Specialties
Showing 337-357 of 1,907 articles
Face Hallucination by Attentive Sequence Optimization with Reinforcement Learning.

Face hallucination is a domain-specific super-resolution problem that aims to generate a high-resolu...

Analyzing DNA methylation patterns in subjects diagnosed with schizophrenia using machine learning methods.

Schizophrenia is a common mental disorder with high heritability. It is genetically complex and to d...

Relative importance of symptoms, cognition, and other multilevel variables for psychiatric disease classifications by machine learning.

This study used machine-learning algorithms to make unbiased estimates of the relative importance of...

Brain Morphometry Methods for Feature Extraction in Random Subspace Ensemble Neural Network Classification of First-Episode Schizophrenia.

Machine learning (ML) is a growing field that provides tools for automatic pattern recognition. The ...

Predicting hospital-acquired pneumonia among schizophrenic patients: a machine learning approach.

BACKGROUND: Medications are frequently used for treating schizophrenia, however, anti-psychotic drug...

Predicting one-year outcome in first episode psychosis using machine learning.

BACKGROUND: Early illness course correlates with long-term outcome in psychosis. Accurate prediction...

Low-rank network signatures in the triple network separate schizophrenia and major depressive disorder.

Brain imaging studies have revealed that functional and structural brain connectivity in the so-call...

The Early Psychosis Screener for Internet (EPSI)-SR: Predicting 12 month psychotic conversion using machine learning.

INTRODUCTION: A faster and more accurate self-report screener for early psychosis is needed to promo...

Resting-state anticorrelated networks in Schizophrenia.

Converging evidences from different lines of research suggest abnormalities in functional brain conn...

Machine learning for predicting psychotic relapse at 2 years in schizophrenia in the national FACE-SZ cohort.

BACKGROUND: Predicting psychotic relapse is one of the major challenges in the daily care of schizop...

From cognitive and clinical substrates to functional profiles: Disentangling heterogeneity in schizophrenia.

The relationship between neurocognition and functioning among patients with schizophrenia is well do...

Disease comorbidity-guided drug repositioning: a case study in schizophrenia.

UNLABELLED: The key to any computational drug repositioning is the availability of relevant data in ...

Machine learning studies on major brain diseases: 5-year trends of 2014-2018.

In the recent 5 years (2014-2018), there has been growing interest in the use of machine learning (M...

Hyponatremia Presenting with Recurrent Mania.

Primary psychogenic polydipsia (PPD) is a chronic, relapsing condition in which there is a disturban...

Supervised machine learning to decipher the complex associations between neuro-immune biomarkers and quality of life in schizophrenia.

Stable phase schizophrenia is characterized by altered patterning in tryptophan catabolites (TRYCATs...

Comparative Evaluation of Machine Learning Strategies for Analyzing Big Data in Psychiatry.

The requirement of innovative big data analytics has become a critical success factor for research i...

Using deep autoencoders to identify abnormal brain structural patterns in neuropsychiatric disorders: A large-scale multi-sample study.

Machine learning is becoming an increasingly popular approach for investigating spatially distribute...

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...

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...

Browse Specialties