An Unsupervised Text Mining Method for Relation Extraction from Biomedical Literature
Author
Abstract
Suggested Citation
DOI: 10.1371/journal.pone.0102039
Download full text from publisher
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Hayda Almeida & Marie-Jean Meurs & Leila Kosseim & Greg Butler & Adrian Tsang, 2014. "Machine Learning for Biomedical Literature Triage," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-21, December.
- Rebecca A. Bernert & Amanda M. Hilberg & Ruth Melia & Jane Paik Kim & Nigam H. Shah & Freddy Abnousi, 2020. "Artificial Intelligence and Suicide Prevention: A Systematic Review of Machine Learning Investigations," IJERPH, MDPI, vol. 17(16), pages 1-25, August.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0102039. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.