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Retrieval-Augmented Generation for Generative Artificial Intelligence in Medicine

Authors :
Yang, Rui
Ning, Yilin
Keppo, Emilia
Liu, Mingxuan
Hong, Chuan
Bitterman, Danielle S
Ong, Jasmine Chiat Ling
Ting, Daniel Shu Wei
Liu, Nan
Publication Year :
2024

Abstract

Generative artificial intelligence (AI) has brought revolutionary innovations in various fields, including medicine. However, it also exhibits limitations. In response, retrieval-augmented generation (RAG) provides a potential solution, enabling models to generate more accurate contents by leveraging the retrieval of external knowledge. With the rapid advancement of generative AI, RAG can pave the way for connecting this transformative technology with medical applications and is expected to bring innovations in equity, reliability, and personalization to health care.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2406.12449
Document Type :
Working Paper