From Data to Decisions: Leveraging Retrieval-Augmented Generation to Balance Citation Bias in Burn Management Literature

(1) Burn injuries demand multidisciplinary, evidence-based care, yet the extensive literature complicates timely decision making. Retrieval-augmented generation (RAG) synthesizes research while addressing inaccuracies in pretrained models. However, citation bias in sourcing for RAG often prioritizes...

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Detaylı Bibliyografya
Asıl Yazarlar:	Ariana Genovese, Srinivasagam Prabha, Sahar Borna, Cesar A. Gomez-Cabello, Syed Ali Haider, Maissa Trabilsy, Cui Tao, Antonio Jorge Forte
Materyal Türü:	Artigo
Dil:	Inglês
Baskı/Yayın Bilgisi:	MDPI AG 2025-06-01
Seri Bilgileri:	European Burn Journal
Konular:	AI (artificial intelligence) large language model RAG (retrieval-augmented generation) burn plastic surgery clinical decision support
Online Erişim:	https://www.mdpi.com/2673-1991/6/2/28
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From Data to Decisions: Leveraging Retrieval-Augmented Generation to Balance Citation Bias in Burn Management Literature

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