Schizophrenia

Illusory generalizability of clinical prediction models.

It is widely hoped that statistical models can improve decision-making related to medical treatments...

Identification of Diagnostic Schizophrenia Biomarkers Based on the Assessment of Immune and Systemic Inflammation Parameters Using Machine Learning Modeling.

UNLABELLED: Disorders of systemic immunity and immune processes in the brain have now been shown to ...

Hallucination: A key challenge to Artificial Intelligence-Generated writing.

Diagnostic deep learning algorithms that use resting EEG to distinguish major depressive disorder, bipolar disorder, and schizophrenia from each other and from healthy volunteers.

BACKGROUND: Mood disorders and schizophrenia affect millions worldwide. Currently, diagnosis is prim...

Computerized analysis of facial expression reveals objective indices of blunted facial affect.

Blunted affect is associated with severe mental illness, particularly schizophrenia. Mechanisms of b...

The future of psychiatry with artificial intelligence: can the man-machine duo redefine the tenets?

As one of the largest contributors of morbidity and mortality, psychiatric disorders are anticipated...

Machine learning techniques in diagnostics and prediction of the clinical features of schizophrenia: a narrative review.

BACKGROUND: Schizophrenia is a severe psychiatric disorder associated with a significant negative im...

Analysis of functional connectivity using machine learning and deep learning in different data modalities from individuals with schizophrenia.

(SCZ) is a severe mental disorder associated with persistent or recurrent psychosis, hallucinations,...

Ecological momentary assessment (EMA) combined with unsupervised machine learning shows sensitivity to identify individuals in potential need for psychiatric assessment.

Ecological momentary assessment (EMA), a structured diary assessment technique, has shown feasibilit...

Peripheral blood MicroRNAs as biomarkers of schizophrenia: expectations from a meta-analysis that combines deep learning methods.

OBJECTIVES: This study aimed at identifying reliable differentially expressed miRNAs (DEMs) for schi...

Differentiating Between Sexual Offending and Violent Non-sexual Offending in Men With Schizophrenia Spectrum Disorders Using Machine Learning.

Forensic psychiatric populations commonly contain a subset of persons with schizophrenia spectrum di...

Automatic identification of schizophrenia employing EEG records analyzed with deep learning algorithms.

Electroencephalography is a method of detecting and analyzing electrical activity in the brain. This...

Detecting schizophrenia with 3D structural brain MRI using deep learning.

Schizophrenia is a chronic neuropsychiatric disorder that causes distinct structural alterations wit...

DeepGenePrior: A deep learning model for prioritizing genes affected by copy number variants.

The genetic etiology of brain disorders is highly heterogeneous, characterized by abnormalities in t...

EEG-based classification of individuals with neuropsychiatric disorders using deep neural networks: A systematic review of current status and future directions.

The use of deep neural networks for electroencephalogram (EEG) classification has rapidly progressed...

Intuitionistic Fuzzy Weighted Least Squares Twin SVMs.

Fuzzy membership is an effective approach used in twin support vector machines (SVMs) to reduce the ...

The Association Between Clozapine Plasma Concentration, CYP2D6 (*10, *2) Polymorphisms and Risk of Adverse Reactions.

BACKGROUND: The aim of this article was to study the relationships between the risk of adverse react...

MS-ACGAN: A modified auxiliary classifier generative adversarial network for schizophrenia's samples augmentation based on microarray gene expression data.

Artificial intelligence-based models and robust computational methods have expedited the data-to-kno...

Generative artificial intelligence: Can ChatGPT write a quality abstract?

ChatGPT is a generative artificial intelligence chatbot which may have a role in medicine and scienc...

Enabling Scientific Reproducibility through FAIR Data Management: An ontology-driven deep learning approach in the NeuroBridge Project.

Scientific reproducibility that effectively leverages existing study data is critical to the advance...

Artificial hallucination: GPT on LSD?