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Artificial Intelligence for Patient Support: Assessing Retrieval-Augmented Generation for Answering Postoperative Rhinoplasty Questions
12
Zitationen
10
Autoren
2025
Jahr
Abstract
This first application of RAG to postoperative rhinoplasty patient care highlights its strengths in accuracy alongside its limitations, including nonresponse and contextual understanding. Addressing these challenges will enable safer, more effective implementation of RAG models across diverse surgical and medical contexts, with the potential to revolutionize patient care by reducing physician workload while enhancing patient engagement.
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