Schizophrenia

Exposotypes in psychotic disorders.

Psychiatry lags in adopting etiological approaches to diagnosis, prognosis, and outcome prediction c...

A novel approach to smart-assisted schizophrenia screening based on Raman spectroscopy and deep learning.

In this study, serum Raman spectra are introduced into the screening of schizophrenia. We collect se...

Multi-model assurance analysis showing large language models are highly vulnerable to adversarial hallucination attacks during clinical decision support.

BACKGROUND: Large language models (LLMs) show promise in clinical contexts but can generate false fa...

MentalAId: an improved DenseNet model to assist scalable psychosis assessment.

BACKGROUND: The escalating mental health crisis during and post-COVID-19 underscores the urgent need...

AI-based prediction of depression symptomatology in first-episode psychosis patients: insights from the EUFEST and RAISE-ETP clinical trials.

BACKGROUND: Depressive symptoms are highly prevalent in first-episode psychosis (FEP) and worsen cli...

Enhancing EEG-Based Schizophrenia Diagnosis with Explainable Multi-Branch Deep Learning.

Schizophrenia poses diagnostic challenges due to a lack of objective assessment. We propose MBSzEEGN...

Brain Oscillations in Bipolar Disorder: Insights from Quantitative EEG Studies.

IntroductionQuantitative electroencephalography (QEEG) is a neurophysiological tool that analyzes br...

Infant rat ultrasonic vocalizations in the neurodevelopmental model of schizophrenia.

Schizophrenia is characterized by early brain developmental abnormalities resulting in, among others...

Genetic predisposition to unwanted side effects under antidepressants and antipsychotics: a molecular-genetic study of 902 patients over 6 weeks.

This project aimed at (1) detailing the complex side effect patterns of 902 inpatients treated for m...

A new framework for mental illnesses diagnosis using wearable devices aided by improved convolutional neural network.

Stress inherent in the modern world is considered one of the main causes of Mental Health Disorders ...

Leveraging stacked classifiers for exploring the role of hedonic processing between major depressive disorder and schizophrenia.

BACKGROUND: Anhedonia, a transdiagnostic feature common to both Major Depressive Disorder (MDD) and ...

Machine Learning-Based Classifier for Identifying Inpatients With Schizophrenia at High Risk of Suicide.

AIMS: The suicide rate of individuals with schizophrenia is higher than the general population. In c...

Predicting clozapine-induced adverse drug reaction biomarkers using machine learning.

Clozapine is an atypical antipsychotic used for patients with treatment-resistant schizophrenia. Thi...

Leveraging computational linguistics and machine learning for detection of ultra-high risk of mental health disorders in youths.

Mental illnesses often manifest through behavioral changes, with speech serving as a key medium for ...

Detecting schizophrenia, bipolar disorder, psychosis vulnerability and major depressive disorder from 5 minutes of online-collected speech.

Psychosis poses substantial social and healthcare burdens. The analysis of speech is a promising app...

The hallucination of learning with generative artificial intelligence.

Foundation models for radiology: fundamentals, applications, opportunities, challenges, risks, and prospects.

Foundation models (FMs) represent a significant evolution in artificial intelligence (AI), impacting...

Mutualistic Multi-Network Noisy Label Learning (MMNNLL) Method and Its Application to Transdiagnostic Classification of Bipolar Disorder and Schizophrenia.

The subjective nature of diagnosing mental disorders complicates achieving accurate diagnoses. The c...

Enhanced schizophrenia detection using multichannel EEG and CAOA-RST-based feature selection.

Schizophrenia is a mental disorder characterized by hallucinations, delusions, disorganized thinking...

Schizophrenia detection from electroencephalogram signals using image encoding and wrapper-based deep feature selection approach.

Schizophrenia is a persistent and serious mental illness that leads to distortions in cognition, per...

Prognostic predictions in psychosis: exploring the complementary role of machine learning models.

BACKGROUND: Predicting outcomes in schizophrenia spectrum disorders is challenging due to the variab...