Schizophrenia

AI as a Novel Digital Stressor in Adolescent Psychosis: Clinical and Ethical Implications.

ObjectiveWith the rapid adoption of artificial intelligence (AI) technologies by adolescents, the impact on their mental health is of critical concern. This article examines the emerging phenomenon of AI-related psychosis, which can be defined as new-onset or exacerbated psychotic experiences associated with generative AI platforms, such as chatbots, avatars, and virtual agents like Siri and Alexa...

Probiotics, psychobiotics, and postbiotics: a therapeutic modality for the management of schizophrenia.

Schizophrenia is a debilitating, chronic neuropsychiatric disorder, a multifactorial disorder combining genetic, neurodevelopmental, immunological, and environmental factors. Common antipsychotic treatments may be effective against positive symptoms, but still lack when dealing with negative symptoms, cognitive defects, and side effects of medication. Recent innovations show how the gut-brain axis...

Development and validation of a prognostic model and risk calculator for the estimation of bipolar-spectrum disorder risk in hospitalised adolescents with non-psychotic/non-bipolar mental disorders.

We aimed to develop and validate a risk estimation model for developing bipolar-spectrum disorders (BSD) in psychiatrically hospitalized adolescents b...

Interrelations between dopaminergic-, gabaergic- and glutamatergic neurotransmitters in antipsychotic-naïve psychosis patients and the association to initial treatment response.

Preclinical evidence points to disturbances in neural networks in psychosis involving interrelations between dopaminergic-, GABAergic- and glutamaterg...

Warning: AI chatbots will soon dominate psychotherapy.

Psychotherapy chatbots have attained remarkable fluency, skill and ubiquity - having become the single most frequent reason people use artificial inte...

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 major depression or schizophrenia under polypharmac...

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 approach for the diagnosis and monitoring of psychosi...

The hallucination of learning with generative artificial intelligence.

From Snapshots to Stable Outcomes: Resting-State Functional Magnetic Resonance Imaging-Based Prognosis of Functioning in Patients With Psychosis Risk or Recent-Onset Depression.

BACKGROUND: Early recovery of functioning is critical for favorable outcomes in psychotic and affective disorders. Transdiagnostic brain activity patt...

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

Foundation models (FMs) represent a significant evolution in artificial intelligence (AI), impacting diverse fields. Within radiology, this evolution ...

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 complex relationship among disorders further exacer...

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, perception, emotions, speech, self-awareness, and act...

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

Schizophrenia is a mental disorder characterized by hallucinations, delusions, disorganized thinking and behavior, and inappropriate affect. Early and...

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

BACKGROUND: Predicting outcomes in schizophrenia spectrum disorders is challenging due to the variability of individual trajectories. While machine le...

A New Insight in Cellular and Molecular Signaling Regulation for Neural Differentiation Program.

Numerous neurological conditions impact the brain, spinal cord, and nerves, including neurodegenerative diseases such as Alzheimer's and Parkinson's d...

Integrating AI and genomics: predictive CNN models for schizophrenia phenotypes.

This study explores the use of deep learning to analyze genetic data and predict phenotypic traits associated with schizophrenia, a complex psychiatri...

Enhancing early detection and treatment of psychosis in Germany: a protocol for the health economic evaluation of an artificial intelligence-guided complex intervention.

INTRODUCTION: Psychosis, characterised by chronic symptoms often emerging in youth, imposes a substantial burden on individuals and healthcare systems...

Evaluating large language models for drafting emergency department encounter summaries.

Large language models (LLMs) possess a range of capabilities which may be applied to the clinical domain, including text summarization. As ambient art...

A robust and scalable framework for hallucination detection in virtual tissue staining and digital pathology.

Histopathological staining of human tissue is essential for disease diagnosis. Recent advances in virtual tissue staining technologies using artificia...

Comparative cytokine signatures and cognitive deficits in early-onset schizophrenia and adolescent major depression: Toward refined diagnostic classification frameworks.

BACKGROUND: This study analyzed plasma cytokine patterns in individuals with schizophrenia (SCZ), major depressive disorder (MDD), and healthy control...