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A controlled trial examining large Language model conformity in psychiatric assessment using the Asch paradigm.

BMC psychiatry
BACKGROUND: Despite significant advances in AI-driven medical diagnostics, the integration of large language models (LLMs) into psychiatric practice presents unique challenges. While LLMs demonstrate high accuracy in controlled settings, their perfor...

Emergent social conventions and collective bias in LLM populations.

Science advances
Social conventions are the backbone of social coordination, shaping how individuals form a group. As growing populations of artificial intelligence (AI) agents communicate through natural language, a fundamental question is whether they can bootstrap...

Identification of Online Health Information Using Large Pretrained Language Models: Mixed Methods Study.

Journal of medical Internet research
BACKGROUND: Online health information is widely available, but a substantial portion of it is inaccurate or misleading, including exaggerated, incomplete, or unverified claims. Such misinformation can significantly influence public health decisions a...

Careful design of Large Language Model pipelines enables expert-level retrieval of evidence-based information from syntheses and databases.

PloS one
Wise use of evidence to support efficient conservation action is key to tackling biodiversity loss with limited time and resources. Evidence syntheses provide key recommendations for conservation decision-makers by assessing and summarising evidence,...

A comparative analysis of large language models versus traditional information extraction methods for real-world evidence of patient symptomatology in acute and post-acute sequelae of SARS-CoV-2.

PloS one
BACKGROUND: Patient symptoms, crucial for disease progression and diagnosis, are often captured in unstructured clinical notes. Large language models (LLMs) offer potential advantages in extracting patient symptoms compared to traditional rule-based ...

Scientific Evidence for Clinical Text Summarization Using Large Language Models: Scoping Review.

Journal of medical Internet research
BACKGROUND: Information overload in electronic health records requires effective solutions to alleviate clinicians' administrative tasks. Automatically summarizing clinical text has gained significant attention with the rise of large language models....

End-to-end Chinese clinical event extraction based on large language model.

Scientific reports
Clinical event extraction is crucial for structuring medical data, supporting clinical decision-making, and enabling other intelligent healthcare services. Traditional approaches for clinical event extraction often use pipeline-based methods to ident...

COMPASS: Computational mapping of patient-therapist alliance strategies with language modeling.

Translational psychiatry
The therapeutic working alliance is a critical predictor of psychotherapy success. Traditionally, working alliance assessment relies on questionnaires completed by both therapists and patients. In this paper, we present COMPASS, a novel framework to ...

Extracting Multifaceted Characteristics of Patients With Chronic Disease Comorbidity: Framework Development Using Large Language Models.

JMIR medical informatics
BACKGROUND: Research on chronic multimorbidity has increasingly become a focal point with the aging of the population. Many studies in this area require detailed patient characteristic information. However, the current methods for extracting such inf...

The benefits and dangers of anthropomorphic conversational agents.

Proceedings of the National Academy of Sciences of the United States of America
A growing body of research suggests that the recent generation of large language model (LLMs) excel, and in many cases outpace humans, at writing persuasively and empathetically, at inferring user traits from text, and at mimicking human-like convers...