Stansfield, CM;
O'Mara-Eves, A;
Thomas, J;
(2015)
Reducing systematic review workload using text mining: opportunities and pitfalls.
Journal of the European Association for Health Information and Libraries
, 11
(3)
pp. 8-10.
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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.
| Type: | Article |
|---|---|
| Title: | Reducing systematic review workload using text mining: opportunities and pitfalls |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | http://eahil.eu/wp-content/uploads/2014/11/journal... |
| Language: | English |
| Additional information: | This is an open access journal under a CC BY licence, (https://creativecommons.org/licenses/by/4.0/) which means that all content is freely available without charge to the user or his/her institution. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, without asking prior permission from the publisher or the author, but giving appropriate credit. |
| Keywords: | systematic reviews, text mining, study selection, automation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > School of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1476973 |
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