AIMC Topic: Language

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Judgments of learning distinguish humans from large language models in predicting memory.

Scientific reports
Large language models (LLMs) increasingly mimic human cognition in various language-based tasks. However, their capacity for metacognition-particularly in predicting memory performance-remains unexplored. Here, we introduce a cross-agent prediction m...

Evaluating Large Language Models and Retrieval-Augmented Generation Enhancement for Delivering Guideline-Adherent Nutrition Information for Cardiovascular Disease Prevention: Cross-Sectional Study.

Journal of medical Internet research
BACKGROUND: Cardiovascular disease (CVD) remains the leading cause of death worldwide, yet many web-based sources on cardiovascular (CV) health are inaccessible. Large language models (LLMs) are increasingly used for health-related inquiries and offe...

Large Language Model-Enhanced Drug Repositioning Knowledge Extraction via Long Chain-of-Thought: Development and Evaluation Study.

JMIR medical informatics
BACKGROUND: Drug repositioning is a pivotal strategy in pharmaceutical research, offering accelerated and cost-effective therapeutic discovery. However, biomedical information relevant to drug repositioning is often complex, dispersed, and underutili...

Invisible Bias in GPT-4o-mini: Detecting Disparities in AI-Generated Patient Messaging.

Journal of medical systems
Artificial intelligence (AI), specifically large language models (LLM), have gained significant popularity over the last decade with increased performance and expanding applications. AI could improve the quality of patient care in medicine but hidden...

CEAF: Capsule network enhanced feature fusion architecture for Chinese Named Entity Recognition.

PloS one
Chinese Named Entity Recognition (NER) is a fundamental task in the field of natural language processing, where achieving deep semantic mining of nested entities and accurate disambiguation of character-level boundary ambiguities stands as its core c...

LLM ethics benchmark: a three-dimensional assessment system for evaluating moral reasoning in large language models.

Scientific reports
This study establishes a novel framework for systematically evaluating the moral reasoning capabilities of large language models (LLMs) as they increasingly integrate into critical societal domains. Current assessment methodologies lack the precision...

Large Language Models in Lung Cancer: Systematic Review.

Journal of medical Internet research
BACKGROUND: In the era of data and intelligence, artificial intelligence has been widely applied in the medical field. As the most cutting-edge technology, the large language model (LLM) has gained popularity due to its extraordinary ability to handl...

Integrating AI in Pakistani ESL classrooms: Teachers' practices, perspectives, and impact on student performance.

PloS one
The global rise of Artificial Intelligence (AI) in English as a Second Language (ESL) education has shown promise, yet its application in resource-constrained contexts like Pakistan remains underexplored. This study examines the integration of AI too...

Using Large Language Models for Chronic Disease Management Tasks: Scoping Review.

JMIR medical informatics
BACKGROUND: Chronic diseases present significant challenges in health care, requiring effective management to reduce morbidity and mortality. While digital technologies like wearable devices and mobile applications have been widely adopted, large lan...

Referential hallucination and clinical reliability in large language models: a comparative analysis using regenerative medicine guidelines for chronic pain.

Rheumatology international
This study compared language models' responses to open-ended questions on regenerative therapy guidelines for chronic pain, assessing their accuracy, reliability, usefulness, readability, semantic similarity, and hallucination rates. This cross-secti...