Schizophrenia

Development and validation of a precision treatment rules for first-line antipsychotic recommendations in first episode psychosis jointly incorporating effectiveness, side effects and patient preferences.

Selecting first-line antipsychotic medication for first episode of psychosis patients is a very challenging task requiring the clinicians to empirically weight multiple criteria. Precision treatment rules developed using health records offer a pragmatic approach to support clinicians' treatment selection, however, they don't incorporate side effects and patient preferences. We used Electronic Heal...

Views of People With Psychosis About Algorithm-Based Relapse Prediction and Data Sharing: Qualitative Study.

BACKGROUND: Preventing relapses of psychosis is difficult and important. Digital remote monitoring (DRM) systems are being developed and tested to support this. Increasingly, these systems use algorithm-based relapse prediction. Hence, understanding stakeholder views about algorithmic prediction is crucial. Existing qualitative work has explored health professionals' views, but very few studies ha...

Leveraging Large Language Models for Contextual Prioritization of Contaminants of Emerging Concern in Chemical Mixtures.

Effective management of chemical mixtures presents a continuing challenge due to the growing diversity and inadequate characterization of contaminants...

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) and autism spectrum disorder (ASD), have seen a m...

ATEdrug: A reliable human-in-the-loop annotation scheme for aspect term extraction and polarity detection in drug reviews.

Pharmacovigilance is vital for post-market drug safety monitoring. Traditional trials inadequately capture adverse reactions. Patient-generated opinio...

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 (AI) chatbots that people use for practical assis...

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 indicate advanced disease progression or worse disease...

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), and risk may vary by multimorbidity and concomi...

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

Large language models in artificial intelligence to answer patient questions in spine surgery: an evaluation of current evidence.

INTRODUCTION: Large language models (LLMs) are increasingly being explored in healthcare, particularly for enhancing patient education. In spine surge...

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, including in contexts involving emotional support and me...

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

Plasma proteomic biomarkers hold significant promise for enhancing clinical assessments and improving early detection of psychosis conversion; however...

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

IMPORTANCE: While growing evidence implicates synaptic dysfunction as a key pathophysiological mechanism in cognitive impairments in schizophrenia (SC...

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 behavioral symptoms in Alzheimer's disease (AD), despite o...

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 facilitate personalized treatment regimen development a...

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 mechanisms. In our previous machine-learning study, 55 ...

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 fully understood. The identification of reliable bloo...

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 system for automated classification of major psychiatri...

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 early clinical recovery (ECR) is critical for personal...

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 (AI) tools in providing dosing recommendations fo...