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Toward systematic review automation: A practical guide to using machine learning tools in research synthesis

Research output: Contribution to journalReview article

Iain J. Marshall, Byron C. Wallace

Original languageEnglish
Article number163
JournalSystematic Reviews
Volume8
Issue number1
DOIs
Publication statusPublished - 11 Jul 2019

King's Authors

Abstract

Technologies and methods to speed up the production of systematic reviews by reducing the manual labour involved have recently emerged. Automation has been proposed or used to expedite most steps of the systematic review process, including search, screening, and data extraction. However, how these technologies work in practice and when (and when not) to use them is often not clear to practitioners. In this practical guide, we provide an overview of current machine learning methods that have been proposed to expedite evidence synthesis. We also offer guidance on which of these are ready for use, their strengths and weaknesses, and how a systematic review team might go about using them in practice.

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