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arXiv Open Access 2024

Retrieval-Augmented Generation for Generative Artificial Intelligence in Medicine

Rui Yang Yilin Ning Emilia Keppo Mingxuan Liu Chuan Hong +4 lainnya
Lihat Sumber

Abstrak

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.

Topik & Kata Kunci

cs.AI

Penulis (9)

R

Rui Yang

Y

Yilin Ning

E

Emilia Keppo

M

Mingxuan Liu

C

Chuan Hong

D

Danielle S Bitterman

J

Jasmine Chiat Ling Ong

D

Daniel Shu Wei Ting

N

Nan Liu

Format Sitasi

APA MLA BibTeX
Yang, R., Ning, Y., Keppo, E., Liu, M., Hong, C., Bitterman, D.S. et al. (2024). Retrieval-Augmented Generation for Generative Artificial Intelligence in Medicine. https://arxiv.org/abs/2406.12449

Akses Cepat

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Informasi Jurnal
Tahun Terbit
2024
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓