Journal
SYSTEMATIC REVIEWS
Volume 8, Issue -, Pages -Publisher
BMC
DOI: 10.1186/s13643-019-1074-9
Keywords
Machine learning; Natural language processing; Evidence synthesis
Categories
Funding
- UK Medical Research Council (MRC), through its Skills Development Fellowship program [MR/N015185/1]
- National Library of Medicine [R01-LM012086-01A1]
- MRC [MR/N015185/1] Funding Source: UKRI
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available