Systematic review and meta-analysis are powerful tools to provide an unbiased overview of all available literature addressing a specific research question. However, systematic reviews are resource-intensive and due to the increasing rate of publication findings are likely to be out of date when published. To improve speed and quality, methodological innovations and automation tools have emerged to support many steps in the production of evidence syntheses.
This talk focuses on software and tools to automate parts of the systematic review and meta-analysis process to reduce the time required to complete systematic reviews. This talk will cover tools to refine and perform systematic searches, machine learning algorithms to automatically assess citations for relevance and inclusion, text-mining tools to annotate and group articles, tools to extract data from PDFs, and software to assist with meta-analysis.