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Ten tips for a text-mining-ready article: How to improve automated discoverability and interpretability

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...

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Detalles Bibliográficos
Autores principales: Leaman, Robert, Wei, Chih-Hsuan, Allot, Alexis, Lu, Zhiyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289435/
https://www.ncbi.nlm.nih.gov/pubmed/32479517
http://dx.doi.org/10.1371/journal.pbio.3000716
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author Leaman, Robert
Wei, Chih-Hsuan
Allot, Alexis
Lu, Zhiyong
author_facet Leaman, Robert
Wei, Chih-Hsuan
Allot, Alexis
Lu, Zhiyong
author_sort Leaman, Robert
collection PubMed
description 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.
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spelling pubmed-72894352020-06-18 Ten tips for a text-mining-ready article: How to improve automated discoverability and interpretability Leaman, Robert Wei, Chih-Hsuan Allot, Alexis Lu, Zhiyong PLoS Biol Community Page 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. Public Library of Science 2020-06-01 /pmc/articles/PMC7289435/ /pubmed/32479517 http://dx.doi.org/10.1371/journal.pbio.3000716 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
spellingShingle Community Page
Leaman, Robert
Wei, Chih-Hsuan
Allot, Alexis
Lu, Zhiyong
Ten tips for a text-mining-ready article: How to improve automated discoverability and interpretability
title Ten tips for a text-mining-ready article: How to improve automated discoverability and interpretability
title_full Ten tips for a text-mining-ready article: How to improve automated discoverability and interpretability
title_fullStr Ten tips for a text-mining-ready article: How to improve automated discoverability and interpretability
title_full_unstemmed Ten tips for a text-mining-ready article: How to improve automated discoverability and interpretability
title_short Ten tips for a text-mining-ready article: How to improve automated discoverability and interpretability
title_sort ten tips for a text-mining-ready article: how to improve automated discoverability and interpretability
topic Community Page
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289435/
https://www.ncbi.nlm.nih.gov/pubmed/32479517
http://dx.doi.org/10.1371/journal.pbio.3000716
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