Systematic reviews are widely used as a tool for decision making to establish new clinical guidelines. Reviews can be time-consuming, potentially leaving authors with thousands of citations to screen. Software tools for assisting reviewers in this process are available, however, only few use text mining techniques to reduce screening time. In this work, we introduce Twister, a web-based tool for semi-automated literature reviews with broad research questions. We discuss how two text mining techniques can be used to (a) extract data elements from clinical abstracts and (b) how citations can be clustered based on a key phrase-extraction to help reviewers reduce screening time. We present the overall system architecture, design consideration and system implementation.
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