AIMC Topic: Language

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Modern artificial intelligence and large language models in graduate medical education: a scoping review of attitudes, applications & practice.

BMC medical education
BACKGROUND: Artificial intelligence (AI) holds transformative potential for graduate medical education (GME), yet, a comprehensive exploration of AI's applications, perceptions, and limitations in GME is lacking.

Modeling rapid language learning by distilling Bayesian priors into artificial neural networks.

Nature communications
Humans can learn languages from remarkably little experience. Developing computational models that explain this ability has been a major challenge in cognitive science. Existing approaches have been successful at explaining how humans generalize rapi...

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...

A Mixed-Methods Evaluation of LLM-Based Chatbots for Menopause.

Studies in health technology and informatics
The integration of Large Language Models (LLMs) into healthcare settings has gained significant attention, particularly for question-answering tasks. Given the high-stakes nature of healthcare, it is essential to ensure that LLM-generated content is ...

Transformer-Based Multilabel NER Using Wikipedia Corpora in Multiple Languages.

Studies in health technology and informatics
The high cost of manual data labeling and privacy concerns result in a considerable dearth of medical annotations in non-English texts. Recent work by Frank and Kramer [1] introduces an unsupervised approach for constructing an ontology-annotated cor...

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...

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....

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...