AIMC Topic: Large Language Models

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From digital assistants to clinical partners: revolutionizing pediatric urology through large language model-powered decision support and patient education.

World journal of urology
BACKGROUND: Large language models (LLMs) demonstrate increasing potential in healthcare applications, yet their clinical utility in specialized pediatric medicine remains inadequately characterized. This study evaluated LLM performance in pediatric u...

Novel Insights into the Application of Large Language Models in the Diagnosis and Treatment of Complex Cardiovascular Diseases: A Comparative Study.

Journal of medical systems
The rapid evolution of large language models (LLMs) in the medical field, particularly in automating medical tasks and supporting diagnosis and treatment, has shown promising potential. However, their accuracy, comprehensiveness, and safety in managi...

Performance of several large language models when answering common patient questions about type 1 diabetes in children: accuracy, comprehensibility and practicality.

BMC pediatrics
BACKGROUND: The use of large language models (LLMs) in healthcare has expanded significantly with advances in natural language processing. Models, such as ChatGPT and Google Gemini, are increasingly used to generate human-like responses to questions,...

Large Language Models: A Paradigm Shift for Dementia Diagnosis and Care.

British journal of hospital medicine (London, England : 2005)
Dementia poses major challenges to healthcare worldwide. Traditional diagnostics rely on lengthy assessments, and access to specialist clinicians is limited. Large language models (LLMs), like Generative Pre-trained Transformer 4 (GPT-4) present new ...

Decoding trust in large language models for healthcare in Saudi Arabia.

Scientific reports
This study investigates the factors influencing user trust and decision-making when using Artificial Intelligence (AI) systems, specifically focusing on ChatGPT in the healthcare domain within the Saudi context. As AI-powered conversational agents ar...

On the effectiveness of limited-data large language model fine-tuning for Arabic.

PloS one
This paper presents an investigation into fine-tuning large language models (LLMs) for Arabic natural language processing (NLP) tasks. Although recent multilingual LLMs have made remarkable progress in zero-shot and few-shot settings, specialized mod...

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...

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...