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

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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Bibliographic Details
Main Authors: Ariana Genovese, Srinivasagam Prabha, Sahar Borna, Cesar A. Gomez-Cabello, Syed Ali Haider, Maissa Trabilsy, Cui Tao, Antonio Jorge Forte
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:European Burn Journal
Subjects:
AI (artificial intelligence)
large language model
RAG (retrieval-augmented generation)
burn
plastic surgery
clinical decision support
Online Access:https://www.mdpi.com/2673-1991/6/2/28
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