版权说明 操作指南
首页 > 成果 > 详情

Dual retrieving and ranking medical large language model with retrieval augmented generation

认领
导出
Link by DOI
反馈
分享
QQ微信 微博
成果类型:
期刊论文
作者:
Qimin Yang;Huan Zuo;Runqi Su;Hanyinghong Su;Tangyi Zeng;...
通讯作者:
Zhiyi Chen<&wdkj&>Tao Tan
作者机构:
[Qimin Yang; Runqi Su; Rongsheng Wang; Jiexin Chen; Yijun Lin; Tao Tan] Faculty of Applied Sciences, Macao Polytechnic University, Macao, China
[Hanyinghong Su] School of Public Health, University of South China, Hengyang, China
[Tangyi Zeng; Huimei Zhou] The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, China
Key Laboratory of Medical Imaging Precision Theranostics and Radiation Protection, College of Hunan Province, The Affiliated Changsha Central Hospital, University of South China, Changsha, China
Department of Medical Imaging, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, China
通讯机构:
[Zhiyi Chen] S
[Tao Tan] F
School of Public Health, University of South China, Hengyang, China<&wdkj&>The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, China<&wdkj&>Key Laboratory of Medical Imaging Precision Theranostics and Radiation Protection, College of Hunan Province, The Affiliated Changsha Central Hospital, University of South China, Changsha, China<&wdkj&>Department of Medical Imaging, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, China<&wdkj&>Faculty of Applied Sciences, Macao Polytechnic University, Macao, China
语种:
英文
关键词:
Medical-large language model;Artificial intelligence (AI);Retrieval-augmented generation (RAG)
期刊:
Scientific Reports
ISSN:
2045-2322
年:
2025
卷:
15
期:
1
机构署名:
本校为通讯机构
院系归属:
公共卫生学院
摘要:
Recent advancements in large language models (LLMs) have significantly enhanced text generation across various sectors; however, their medical application faces critical challenges regarding both accuracy and real-time responsiveness. To address these dual challenges, we propose a novel two-step retrieval and ranking retrieval-augmented generation (RAG) framework that synergistically combines embedding search with Elasticsearch technology. Built upon a dynamically updated medical knowledge base incorporating expert-reviewed documents from leading healthcare institutions, our hybrid architectur...

反馈

验证码:
看不清楚,换一个
确定
取消

成果认领

标题:
用户 作者 通讯作者
请选择
请选择
确定
取消

提示

该栏目需要登录且有访问权限才可以访问

如果您有访问权限,请直接 登录访问

如果您没有访问权限,请联系管理员申请开通

管理员联系邮箱:yun@hnwdkj.com