Schizophrenia

MedFusionT5: Cross-Modal Attention Boosts Semantic Quality and Reduces Hallucinations in Dental AI.

INTRODUCTION AND AIMS: Automated dental report generation faces significant challenges in multimodal fusion, often resulting in suboptimal semantic quality and risks of hallucination, where AI generates clinically unsupported content. Current approaches that rely on simple feature concatenation or bidirectional attention mechanisms fail to effectively capture visual-textual relationships in medica...

Integration of AI and Neuroscience: New Methods in Studying the Causes of Mental Disorders.

ObjectiveThis review sought to systematize knowledge about the use of artificial intelligence in neurobiological research of mental disorders and assess its potential in identifying their causes.MethodsA qualitative synthesis of scientific literature from the Scopus and Web of Science databases for 2020-2024 was conducted. A total of 50 sources were selected, including papers describing the use of...

Diagnostic Utility of Formal Thought Disorder Between Affective and Non-Affective Psychosis: A Machine Learning Approach.

Harnessing exosomes for precision diagnostics and therapies in psychiatry disorders.

Exosomes are nanosized extracellular vesicles enriched with proteins, lipids, and nucleic acids and are emerging as powerful mediators of intercellula...

A Novel Hybrid Large Language Model Approach for Reporting Panoramic Radiographs and Performance Comparison with Current Large Language Models.

Large language models (LLMs) show potential in clinical reporting, yet current multimodal systems remain unreliable for interpreting panoramic radiogr...

Artificial Intelligence and CT Neuroimaging in Dementia and Psychotic Disorders: A Viewpoint.

Psychotic disorders are marked by heterogeneity in symptoms and treatment response, yet efforts to develop clinically useful predictive models through...

A systematic review on dysconnectivity in face and emotion processing networks in schizophrenia.

Schizophrenia is a complex psychiatric disorder that affects approximately 20 million people worldwide. Patients show face-processing deficits that si...

Integrative Molecular Pattern Learning for Mental Disorders Via Dual-Effect Matrix-Enabled Multiomics Platform.

Mental health issues are surging in contemporary society, especially among adolescents and adults, harming well-being and social functioning. Objectiv...

Differentiating bipolar disorder and schizophrenia using sleep EEG power and coherence features: A machine learning approach based on polysomnography.

Differentiating between bipolar disorder (BD) and schizophrenia (SZ) is challenging due to overlapping clinical symptoms and shared genetic risks, res...

Hallucination filtering in radiology vision-language models using discrete semantic entropy.

OBJECTIVE: To determine whether using discrete semantic entropy (DSE) to reject questions likely to generate hallucinations can improve the accuracy o...

Identifying Transdiagnostic Predictors of Depression Across Psychoses: Informing Stratified Antidepressant Treatments.

INTRODUCTION: Depression frequently co-occurs with psychosis and is associated with poor outcomes. Early identification of patients at risk of persist...

Looking back to the future of psychiatry: reflections on an international sojourn.

Psychiatry's metamorphosis continues to evolve over time as concepts of the brain's neuronal function and the complexity of the mind interact with rap...

Prediction models for suicide reattempts by lasso regression through machine learning models: Single versus multiple suicide attempters.

The best predictor of a suicide attempt is a previous attempt, apart from psychiatric diagnoses also associated. Some studies found other indicators o...

Predicting treatment response in psychosis using fMRI: A comprehensive review.

In recent years, the use of functional Magnetic Resonance Imaging (fMRI) methods to predict treatment response in schizophrenia (SCZ) through statisti...

Integrating qHTS and QSAR Models to Identify Safe GPCR-Targeted Compounds: A Focus on hERG-Dependent Cardiotoxicity.

G-protein-coupled receptors (GPCRs) are a diverse family of seven-transmembrane domain receptors that play pivotal roles in various physiological and ...

Threat discrimination of real-world social interactions in schizotypal traits.

Threat detection is compromised across the schizophrenia spectrum, often revealed by paranoia and delusions. Threat difficulties extend to nonclinical...

De novo design of GPCR exoframe modulators.

G-protein-coupled receptors (GPCRs) are important therapeutic targets and have been targeted mainly through their orthosteric site, where the endogeno...

Interconnected Cognitive and Neuroimmune Impairments in Schizophrenia: Modulating Effects of Antipsychotic Type, Illness Duration, and Symptom Severity.

OBJECTIVE: Cognitive impairment in schizophrenia (SCZ) is associated with neuroinflammation and neurotrophic dysregulation. The role of pro-inflammato...

Neuroimaging-derived brain age as a new promising biomarker in mental disorders.

Mental disorders are frequently associated with accelerated brain aging, yet the diagnostic and classificatory utility of brain age remains uncertain....

Improved schizophrenia detection using structural MRI with multi-scale transform and deep orthogonal features.