Reducing systematic review workload using text mining: opportunities and pitfalls
Abstract
This EAHIL workshop focussed on three applications of text mining to assist with screening citations for systematic reviews, and encouraged participants to discuss issues affecting their adoption. This paper outlines these applications and summarises the factors raised by participants in relation to their uptake. Key aspects to uptake include having an accepted advantage over existing approaches, coupled with training and user support.
References
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M, Ananiadou S. Using text mining for study
identification in systematic reviews: a systematic
review of current approaches. Systematic
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2. Project Transform [internet] 2015 [cited 2015 Jun
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3. Thomas JM. Diffusion of innovation in systematic
review methodology: Why is study selection not
yet assisted by automation? OA Evidence-Based
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4. Rogers E. Diffusion of innovations. 5th ed. New
York, NY: Free Press; 2003.
M, Ananiadou S. Using text mining for study
identification in systematic reviews: a systematic
review of current approaches. Systematic
Reviews. 2015;4:5. doi:10.1186/2046-4053-4-5
2. Project Transform [internet] 2015 [cited 2015 Jun
30] http://community.cochrane.org/transform
3. Thomas JM. Diffusion of innovation in systematic
review methodology: Why is study selection not
yet assisted by automation? OA Evidence-Based
Medicine. 2013 Oct;1(2):12.
4. Rogers E. Diffusion of innovations. 5th ed. New
York, NY: Free Press; 2003.
Published
2016-03-11
How to Cite
1.
Stansfield C. Reducing systematic review workload using text mining: opportunities and pitfalls. JEAHIL [Internet]. 11Mar.2016 [cited 19Apr.2024];11(3). Available from: http://ojs.eahil.eu/ojs/index.php/JEAHIL/article/view/53
Issue
Section
Workshop Report
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