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CPRS:一个基于LLMs的临床协议推系统

Jingkai Ruan¹, Qianmin Su², Zihang Chen¹

¹School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, ShangHai, China.

International journal of medical informatics

|December 7, 2024

概括

本研究介绍了使用大型语言模型 (LLM) 和知识图的临床试验协议推系统. 该系统增强了患者与协议匹配的效率和准确性,推动了临床试验的开发.

科学领域:

人工智能在医学中的应用
临床试验管理临床试验管理

背景情况:

临床试验协议对于指导研究目标至关重要.
大型语言模型 (LLM) 为研究建议提供先进的语义功能.

研究的目的:

开发一种新的临床试验协议推系统.
利用GPT-4和知识图来改善患者与协议的匹配.

主要方法:

开发了一个结合GPT-4和知识图的系统.
知识图标识了类似的临床试验项目.
GPT-4提供了基于语义分析的针对性患者建议.

主要成果:

在根据相似性对协议进行排序方面,GPT-4的表现优于SBERT模型.
该系统证明了对患者进行更高的匹配效率和准确性.
该系统有助于对临床试验协议建议的自动化.

结论:

整合知识图和LLM可以提高对临床试验数据的理解和处理.
该系统提高了对患者协议建议的匹配效率和准确性.
这种方法自动化了对医学研究和公共卫生至关重要的建议.

关键词:

临床试验临床试验是指临床试验的临床试验.知识图表知识图表在法律上,LLMs.推系统是推系统.

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