Skip Navigation

Bioinformatics 2006 22(14):e446-e453; doi:10.1093/bioinformatics/btl235
This Article
Right arrow FREE Full Text (Print PDF) Freely available
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Google Scholar
Right arrow Articles by Shatkay, H.
Right arrow Articles by Blostein, D.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Shatkay, H.
Right arrow Articles by Blostein, D.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org

Integrating image data into biomedical text categorization

Hagit Shatkay *, Nawei Chen and Dorothea Blostein

School of Computing, Queen's University Kingston, Ontario, Canada

*To whom correspondence should be addressed.

Categorization of biomedical articles is a central task for supporting various curation efforts. It can also form the basis for effective biomedical text mining. Automatic text classification in the biomedical domain is thus an active research area. Contests organized by the KDD Cup (2002) and the TREC Genomics track (since 2003) defined several annotation tasks that involved document classification, and provided training and test data sets. So far, these efforts focused on analyzing only the text content of documents. However, as was noted in the KDD'02 text mining contest—where figure-captions proved to be an invaluable feature for identifying documents of interest—images often provide curators with critical information. We examine the possibility of using information derived directly from image data, and of integrating it with text-based classification, for biomedical document categorization. We present a method for obtaining features from images and for using them—both alone and in combination with text—to perform the triage task introduced in the TREC Genomics track 2004. The task was to determine which documents are relevant to a given annotation task performed by the Mouse Genome Database curators. We show preliminary results, demonstrating that the method has a strong potential to enhance and complement traditional text-based categorization methods.

Contact: shatkay{at}cs.queensu.ca


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 BioinformaticsHome page
S. Xu, J. McCusker, and M. Krauthammer
Yale Image Finder (YIF): a new search engine for retrieving biomedical images
Bioinformatics, September 1, 2008; 24(17): 1968 - 1970.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
Y. Qian and R. F. Murphy
Improved recognition of figures containing fluorescence microscope images in online journal articles using graphical models
Bioinformatics, February 15, 2008; 24(4): 569 - 576.
[Abstract] [Full Text] [PDF]

Home page
 Brief BioinformHome page
P. Zweigenbaum, D. Demner-Fushman, H. Yu, and K. B. Cohen
Frontiers of biomedical text mining: current progress
Brief Bioinform, October 30, 2007; (2007) bbm045v1.
[Abstract] [Full Text] [PDF]


Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.