Retrieval-Augmented Generation for Generative Artificial Intelligence in Medicine

Autor: Yang, Rui, Ning, Yilin, Keppo, Emilia, Liu, Mingxuan, Hong, Chuan, Bitterman, Danielle S, Ong, Jasmine Chiat Ling, Ting, Daniel Shu Wei, Liu, Nan
Rok vydání: 2024
Předmět:
Druh dokumentu: Working Paper
Popis: 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.
Databáze: arXiv