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- Title
Ten tips for a text-mining-ready article: How to improve automated discoverability and interpretability.
- Authors
Leaman, Robert; Wei, Chih-Hsuan; Allot, Alexis; Lu, Zhiyong
- Abstract
Data-driven research in biomedical science requires structured, computable data. Increasingly, these data are created with support from automated text mining. Text-mining tools have rapidly matured: although not perfect, they now frequently provide outstanding results. We describe 10 straightforward writing tips—and a web tool, PubReCheck—guiding authors to help address the most common cases that remain difficult for text-mining tools. We anticipate these guides will help authors' work be found more readily and used more widely, ultimately increasing the impact of their work and the overall benefit to both authors and readers. PubReCheck is available at http://www.ncbi.nlm.nih.gov/research/pubrecheck. Your published research is already being processed with automated tools, and text mining will become more common; this Community Page article describes how you can help these tools process your work more accurately, including a web tool, PubReCheck.
- Subjects
MEDICAL sciences; AUTHOR-reader relationships; WORK in process; MEDICAL research
- Publication
PLoS Biology, 2020, Vol 18, Issue 6, p1
- ISSN
1544-9173
- Publication type
Article
- DOI
10.1371/journal.pbio.3000716