An External Validation Study on Two Pre-Trained Large Language Models for Multimodal Prognostication in Laryngeal and Hypopharyngeal Cancer: Integrating Clinical, Treatment, and Radiomic Data to Predict Survival Outcomes with Interpretable Reasoning

<b>Background:</b> Laryngeal and hypopharyngeal cancers (LHCs) exhibit heterogeneous outcomes after definitive radiotherapy (RT). Large language models (LLMs) may enhance prognostic stratification by integrating complex clinical and imaging data. This study validated two pre-trained LLMs—GPT-4o-2024...

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Auteurs principaux:	Wing-Keen Yap, Shih-Chun Cheng, Chia-Hsin Lin, Ing-Tsung Hsiao, Tsung-You Tsai, Wing-Lake Yap, Willy Po-Yuan Chen, Chien-Yu Lin, Shih-Ming Huang
Format:	Artigo
Langue:	Inglês
Publié:	MDPI AG 2025-12-01
Collection:	Bioengineering
Sujets:	large language models laryngeal cancer hypopharyngeal cancer radiomics prognosis survival prediction
Accès en ligne:	https://www.mdpi.com/2306-5354/12/12/1345
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