Application of Automated Literature Screening Tools in Systematic Reviews

Abstract

Systematic reviews are the basis of evidence-based medical research, and high-quality systematic reviews represent the highest level of evidence for evaluating treatment effects. Traditional systematic reviews are mainly done manually, but the reading and screening of massive literature requires a lot of energy and time for clinicians, resulting in low efficiency, which cannot meet the needs of rapid decision-making. To address this problem, a number of automated tools have been developed. Thus, this article aims to systematically sort out existing automated tools for systematic review literature screening, and analyze their respective performance, characteristics, and usage to understand the current development status of this field and provide reference for related research and applications.

Keywords

• systematic review
• machine learning
• artificial intelligence
• literature screening tool
• evidence-based medicine