Psychiatry

Schizophrenia

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

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RNA Editing Signatures Powered by Artificial Intelligence: A New Frontier in Differentiating Schizophrenia, Bipolar, and Schizoaffective Disorders.

Mental health disorders are devastating illnesses, often misdiagnosed due to overlapping clinical sy...

Reevaluating feature importances in machine learning models for schizophrenia and bipolar disorder: The need for true associations.

Skorobogatov et al. developed supervised machine learning models to predict diagnoses and illness st...

Facial expression analysis using convolutional neural network for drug-naive and chronic schizophrenia.

OBJECTIVE: Facial images have been shown to convey mental conditions as clinical symptoms. This stud...

Evolution of Linguistic Markers of Agency, Centrality and Content During Metacognitive Therapy for Psychosis: A Pilot Exploratory Study.

AIM: Metacognitive Reflection and Insight Therapy (MERIT) is a form of person-centred psychotherapy ...

The Role of Artificial Intelligence in Obesity Medicine.

The rising prevalence of obesity presents significant health, economic, and social challenges, neces...

Improved patient identification by incorporating symptom severity in deep learning using neuroanatomic images in first episode schizophrenia.

Brain alterations associated with illness severity in schizophrenia remain poorly understood. Establ...

Multi-Loss Disentangled Generative-Discriminative Learning for Multimodal Representation in Schizophrenia.

Schizophrenia (SCZ) is a multifactorial mental illness, thus it will be beneficial for exploring thi...

Subcortical and insula functional connectivity aberrations and clinical implications in first-episode schizophrenia.

INTRODUCTION: Schizophrenia is a complex mental disorder whose pathophysiology remains elusive, part...

Classification of psychosis spectrum disorders using graph convolutional networks with structurally constrained functional connectomes.

This article considers the problem of classifying individuals in a dataset of diverse psychosis spec...

Identification of Bipolar Disorder and Schizophrenia Based on Brain CT and Deep Learning Methods.

With the increasing prevalence of mental illness, accurate clinical diagnosis of mental illness is c...

Magnetic resonance imaging-based machine learning classification of schizophrenia spectrum disorders: a meta-analysis.

BACKGROUND: Recent advances in multivariate pattern recognition have fostered the search for reliabl...

Automated linguistic analysis in youth at clinical high risk for psychosis.

Identifying individuals at clinical high risk for psychosis (CHRP) is crucial for preventing psychos...

Optimizing graph neural network architectures for schizophrenia spectrum disorder prediction using evolutionary algorithms.

BACKGROUND AND OBJECTIVE: The accurate diagnosis of schizophrenia spectrum disorder plays an importa...

Cognitive profiles across the psychosis continuum.

Cognitive impairments are core features in individuals across the psychosis continuum and predict fu...

Prediction of anhedonia in patients with first-episode schizophrenia using a Wavelet-ALFF-based Support vector regression model.

Anhedonia is one of the core features of the negative symptoms of schizophrenia and can be extremely...

Forecasting the incidence frequencies of schizophrenia using deep learning.

Mental disorders are becoming increasingly prevalent worldwide, and accurate incidence forecasting i...

Schizophrenia diagnosis using the GRU-layer's alpha-EEG rhythm's dependability.

Verifying schizophrenia (SZ) can be assisted by deep learning techniques and patterns in brain activ...

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