Enhancing Clinical Decision Support with Adaptive Iterative Self-Query Retrieval for Retrieval-Augmented Large Language Models

Retrieval-Augmented Generation (RAG) offers a promising strategy to harness large language models (LLMs) for delivering up-to-date, accurate clinical guidance while reducing physicians’ cognitive burden, yet its effectiveness hinges on query clarity and structure. We propose an adaptive Self-Query R...

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Principais autores:	Srinivasagam Prabha, Cesar A. Gomez-Cabello, Syed Ali Haider, Ariana Genovese, Maissa Trabilsy, Nadia G. Wood, Sanjay Bagaria, Cui Tao, Antonio J. Forte
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2025-08-01
Series:	Bioengineering
Assuntos:	self-query retrieval retrieval-augmented generation large language models clinical decision support decision support systems
Acceso en liña:	https://www.mdpi.com/2306-5354/12/8/895
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