自然语言处理在系统评价中的应用

Application of nature language processing in systematic reviews

系统评价可为临床实践和医疗卫生决策提供重要证据支持。但在系统评价的制作过程中,文献筛选和数据提取是非常耗时的工作步骤。自然语言处理(NLP),作为计算机科学和人工智能的研究方向之一,可加速系统评价中的文献筛选和数据提取过程。本文回顾了系统评价对快速文献筛选和数据提取的需求;介绍了NLP的发展历程和机器学习类型,系统整理了现有可用于系统评价初筛、全文筛选和数据提取过程的NLP工具;讨论了现有NLP在系统评价领域应用时存在的问题,并对其未来发展提出了展望。

Systematic reviews can provide important evidence support for clinical practice and health decisionmaking.In this process,literature screening and data extraction are extensively time-consuming procedures.Natural language processing(NLP),as one of the research directions of computer science and artificial intelligence,can accelerate the process of literature screening and data extraction in systematic reviews.This paper introduced the requirements of systematic reviews for rapid literature screening and data extraction,the development of NLP and types of machine learning;and systematically collated the NLP tools for the title and abstract screening,full-text screening and data extraction in systematic reviews;and discussed the problems in the application of NLP tools in the field of systematic reviews and proposed a prospect for its future development.