LLM evaluation for thyroid nodule assessment: comparing ACR-TIRADS, C-TIRADS, and clinician-AI trust gap

ObjectiveTo evaluate the diagnostic performance and clinical utility of advanced large language models (LLMs) -GPT-4o, GPT-o3-mini, and DeepSeek-R1- in stratifying thyroid nodule malignancy risk and generating guideline-aligned management recommendations based on structured narrative ultrasound desc...

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Detalhes bibliográficos

Principais autores:	Xi Dai, Yu Xi, Yong Hu, Qingyan Ding, Yu Zhang, Hui Liu, Piaofei Chen, Xi Wang, Wenjun Wang, Chaoxue Zhang
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Frontiers Media S.A. 2025-09-01
coleção:	Frontiers in Endocrinology
Assuntos:	large language models (LLMs) thyroid nodules risk stratification ACR-TIRADS C-TIRADS clinical decision-making
Acesso em linha:	https://www.frontiersin.org/articles/10.3389/fendo.2025.1667809/full
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