Schizophrenia

Large Language Models for Breast and Cervical Cancers Communication: Mixed Methods Evaluation Study Assessing Linguistic Quality, Safety, and Accessibility.

BACKGROUND: Effective communication about breast and cervical cancers remains a public health challenge, with widespread misinformation and barriers to cancer-related language understanding. Large language models (LLMs) offer potential for scalable health communication, yet trade-offs between quality, safety, and accessibility of general-purpose and medical-domain LLMs remain underexplored. OBJECT...

Large Language Model Summarization of Physician-to-Physician Calls for Interhospital Transfer of Patients With ST-Elevation Myocardial Infarction: Observational Study.

BACKGROUND: Interhospital transfer of patients with suspected ST-elevation myocardial infarction (STEMI) requires timely and robust communication. Clinical uptake of potentially useful information from physician-to-physician phone calls authorizing transfer is low at many institutions, at least in part due to relative inaccessibility of call audio and lack of transcripts or summaries. Large langua...

Expression patterns of risk genes associated with three evolutionarily relevant syndromes in rhesus macaque and human brains.

Depressive disorder (DD), Alzheimer's disease (AD), and schizophrenia (SZ) are evolutionarily relevant traits that disrupt neural networks supporting ...

Comprehensive analysis of interactions between brain aging and late-onset psychoses using heuristic mapping models.

BACKGROUND: Advanced brain aging is closely associated with late-onset psychoses, including bipolar disorder(BD), schizophrenia(SP), and major depress...

An integrative NLP framework identifies multilevel linguistic phenotypes of schizophrenia across tasks.

BACKGROUND: Linguistic abnormalities in schizophrenia (SCZ) span morphological, syntactic, semantic, and discourse levels. Converging cross-linguistic...

Fabricated references due to artificial intelligence hallucination in the European Journal of Cardiovascular Nursing: Also here nurses are the most trustable profession.

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 ass...

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 servi...

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...