Systematic reviews can provide important evidence support for clinical practice and health decision-making. 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.
Citation： QIN Xuan, LIU Jiali, WANG Yuning, DENG Ke, MA Yu, ZOU Kang, LI Ling, SUN Xin. Application of nature language processing in systematic reviews. Chinese Journal of Evidence-Based Medicine, 2021, 21(6): 715-720. doi: 10.7507/1672-2531.202012150 Copy