Schizophrenia

Evaluating Public Sentiment on Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder Compared With Other Mental Health Disorders From Posts on X (Formerly Known as Twitter): Longitudinal Analysis.

BACKGROUND: Neurodevelopmental disorders, especially attention-deficit/hyperactivity disorder (ADHD)...

Is Deep Learning Ready for Abdominal Organ-at-Risk Segmentation in the Foundation Model Era: A Comprehensive Study of Challenging Clinical Cases.

PURPOSE: The application of deep learning-based methods for accurate organ-at-risk segmentation in c...

It Is the Journey, Not the Destination: Moving From End Points to Trajectories When Assessing Chatbot Mental Health Safety.

Large language models are rapidly becoming embedded in everyday life through artificial intelligence...

Presence hallucination induction through robotically mediated somatomotor conflicts: A pooled analysis of 25 experiments.

Hallucinations are significant symptoms in psychiatric and neurodegenerative diseases, that may indi...

Multimorbidity and major adverse cardiovascular events in antipsychotic users: Time-to-event prediction by explainable machine learning.

Antipsychotic treatment is associated with higher risk of major adverse cardiovascular events (MACEs...

Second-to-fourth digit (2D:4D) ratio and criminal involvement in schizophrenia.

Glucagon-Like Peptide-1 Receptor Agonists in Psychiatry: A Pharmacoepidemiological Scoping Review.

Pharmacoepidemiological studies have expanded the capacity to detect therapeutic benefits and advers...

Neurobiological Signatures of Trauma, Personality, and Depressivity: A Transdiagnostic Machine Learning Study in Adolescents and Young Adults.

BACKGROUND: Adolescence and early adulthood are periods of increased vulnerability for psychiatric d...

Mass Media Narratives of Psychiatric Adverse Events Associated With Generative AI Chatbots: Rapid Scoping Review.

BACKGROUND: Generative artificial intelligence (AI) chatbots have rapidly entered public use, includ...

Blood plasma proteomic biomarkers for forecasting transition to psychosis in an Asian cohort.

Plasma proteomic biomarkers hold significant promise for enhancing clinical assessments and improvin...

Bridging the Scales via Personalized Cellular Modeling and Deep Phenotyping in Schizophrenia.

IMPORTANCE: While growing evidence implicates synaptic dysfunction as a key pathophysiological mecha...

Comparative Mortality Risk of Aripiprazole, Olanzapine, Quetiapine, and Risperidone in Alzheimer's Disease: A Real‑World Retrospective Cohort Study with Treatment Effect Heterogeneity Analysis.

BACKGROUND: Second-generation antipsychotics (SGAs) are frequently used off-label to manage behavior...

Predicting future mortality risk in first-episode psychosis: External validation of the MIRACLE-FEP machine learning model.

BACKGROUND: Identifying patients with first-episode psychosis (FEP) at high mortality risk may facil...

Severity matters: Using network analysis to explain low and high levels of persecutory beliefs.

Delusions, including persecutory beliefs, are theorised to arise from multifaceted interacting mecha...

Machine learning-based predictive models and subtypes patterns in peripheral blood of schizophrenia based on a machine learning computational framework.

Schizophrenia (SCZ) is a complex psychiatric disorder, and its pathogenic mechanisms are not yet ful...

Multi-domain ECG feature extraction enable accurate automated recognition of bipolar disorder, depression and schizophrenia.

OBJECTIVE: To develop and validate a multi-lead electrocardiogram (ECG)-based machine learning syste...

Predicting early clinical recovery in first-episode psychosis: development and external validation of a clinically interpretable multivariable model.

BACKGROUND: Identifying patients with first-episode psychosis (FEP) who are unlikely to achieve earl...

Assessing the accuracy of 4 generative AI tools to guide dosing of long-acting injectable antipsychotics.

PURPOSE: The purpose of this study was to review the accuracy of 4 different artificial intelligence...

Attitudes toward artificial intelligence among individuals with anxiety, depression, bipolar disorders, and schizophrenia.

BACKGROUND: Artificial intelligence (AI) increasingly supports medical diagnosis, interventions, and...

Exploring brain lobe-specific insights in an explainable framework for EEG-based schizophrenia detection.

Schizophrenia (ScZ) is a growing global health concern that affects millions of people and puts seve...

Anticipating incomplete patient-reported outcomes in schizophrenia: a machine learning approach to predict the occurrence of missing data.