Schizophrenia

Data-Driven Profiles of Youth Executive Function and Their Longitudinal Associations With Externalizing Problems.

OBJECTIVE: Executive function (EF) deficits are observed in externalizing disorders. However, research has yet to explore the specificity of these associations for externalizing symptom dimensions and their potential utility in identifying subgroups of youth at risk for persistent problems. The current study leverages unsupervised learning methods to investigate longitudinal relationships between ...

Automated Summarization of Military Medical Records Using AI: Evaluation Via the OPTICA Framework.

INTRODUCTION: Military medical fitness evaluations require physicians to rapidly review extensive and heterogeneous medical records to determine service eligibility and duty limitations. This process is time-consuming, cognitively demanding, and often conducted under significant operational pressure, contributing to inefficiencies and physician burnout. Advances in artificial intelligence (AI), pa...

Functional Outcome Prediction in Young Adults With Mental Health Symptoms Using Machine Learning and Large Language Models: Longitudinal Observational Study.

BACKGROUND: Functional impairments associated with mental health conditions are on the rise. Predicting functional outcomes may improve the targeting ...

Large language model applications in facial plastic and reconstructive surgery: a systematic review of applications, performance, and ethical considerations.

BACKGROUND: Artificial intelligence (AI)-powered large language models (LLMs) are increasingly used as adjunctive tools in education, research, and pa...

A reproducible statistical evaluation framework for large-sample assessment of AI-generated medical references: cross-platform application of the reference hallucination score.

OBJECTIVE: To quantitatively evaluate the bibliographic reliability of AI-generated medical references across multiple chatbot platforms using the Ref...

Evaluation of Five Large Language Models for Parental Education in Pediatric Anesthesia: Reliability and Readability Study.

BACKGROUND: Although large language models (LLMs) show potential for patient education, their accuracy, usability, and comprehensibility lack validati...

Ethical Considerations in Personal Health Large Language Models.

Personal health large language models (PH-LLMs) have rapidly evolved from research prototypes into consumer-facing, data-linked systems that support s...

Using AI to Detect Psychosis Relapse: Scoping Review.

BACKGROUND: Psychotic disorder represents a leading cause of disability worldwide, and relapse in psychosis is common. Artificial intelligence (AI) is...

Towards a rational ECT treatment approach for severe and treatment resistant schizophrenia using neuroimaging biomarkers: A focused review.

Treatment resistant schizophrenia (TRS) is a major challenge in psychiatry, and its management remains an unmet need. Given the relatively high preval...

Decoding common and rare noncoding variant effects across cellular and developmental contexts.

Interpreting how noncoding variants act in specific cell types across human development is a major challenge. Here we generated 3 billion predictions ...

Performance of large language models in interpreting evidence-based clinical guidelines for lumbar disc herniation with radiculopathy.

OBJECTIVE: Large language models (LLMs) are increasingly used as clinical information tools; however, their ability to accurately interpret evidence-b...

Hybrid deep learning model for brain age prediction using time-distributed convolutional and bidirectional LSTM networks.

Brain age prediction has gained significant attention due to its strong correlation with neurological and cognitive disorders. The discrepancy between...

Artificial intelligence (AI) psychosis: mechanisms, clinical risks and safety considerations in generative AI chatbots.

As generative artificial intelligence chatbots become embedded in everyday life, concerns about their psychological risks are growing. Emerging report...

TAFNet: Trusted Multiview Associative Fusion Neural Networks for Analyzing Dynamic Brain Networks.

Dynamic functional connectivity (DFC) is crucial for analyzing brain networks, as it captures the temporal dynamics of brain regions. However, most ex...

Large language models and generative artificial intelligence in endodontics: a scoping review.

The aim of this study is to comprehensively examine the evolution of artificial intelligence (AI), specifically large language models (LLMs), in the f...

The entropic brain today.

Introduced in 2014 and revised in 2018, the entropic brain hypothesis has accrued a wealth of supportive evidence. The hypothesis states that-along a ...

Comparative evaluation of generative AI models for chest radiograph report generation in the emergency department.

OBJECTIVES: To benchmark medical image-specific vision-language models (VLMs) against real-world radiologist-written reports, focusing on diagnostic q...

Predicting transition to psychiatric disorders in clinical high-risk for psychosis subjects using machine learning and facial features.

BACKGROUND: Clinical-high-risk for psychosis (CHR) status is increasingly viewed as a transdiagnostic risk state, but scalable markers of adverse outc...

Large Language Models and Retrieval-Augmented Platforms for Dental Implant Complications: A Blinded, Expert-Rated Benchmarking Study.

OBJECTIVES: To compare expert-rated diagnostic accuracy, patient safety, completeness of management, and freedom from detectable hallucinations across...

Valence-specific oculomotor abnormalities induced by dynamic video stimuli as a robust biomarker for schizophrenia.

BACKGROUND: Deficits in visual attention and emotional processing are core to schizophrenia (SZ). Although oculomotor abnormalities during static view...