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This study aims to evaluate the effect of input format and hyperparameter settings on GPT-5 and explore the contribution of GPT-5 assistance to radiologists' performance in abdominal cases.

Large language models (LLMs) are increasingly applied in medical education, yet their reliability in specialized, high-stakes assessments such as the Chinese Health Professional and Technical Examination remains unclear. DeepSeek-R1, a recently released reasoning-enhanced LLM, has shown promising performance, but empirical evidence within nursing examination contexts is limited.

Gestational diabetes mellitus (GDM) is a prevalent chronic condition that affects maternal and fetal health outcomes worldwide, increasingly in underserved populations. While generative artificial intelligence (AI) and large language models (LLMs) have shown promise in health care, their application in GDM management remains underexplored.

A national transfusion history sharing service, such as the alloantibody exchange, should provide standardized data. However, red cell antigen profiles frequently exist as unstructured text. To reduce human curation and improve scalability, we evaluated whether large language models (LLMs) could standardize free-text antigen profiles.

Tobacco-related misinformation on social media platforms presents growing challenges to digital health communication and public health. Although prior studies have focused on platform-specific patterns, a unified framework for categorizing and comparing misinformation across platforms is lacking. Such a framework is essential for improving infodemiological surveillance and designing targeted digital interventions.

Background

Generative artificial intelligence, particularly large language models (LLMs), is increasingly used to navigate information, potentially shaping users' perceptions of different social groups. This study examines age-related stereotypes in LLM-generated text using natural language processing (NLP) techniques.

This study aims to evaluate various large language models (LLMs) for their effectiveness in answering Japan Radiology Board Examination (JRBE).