TREC genomics special issue overview
Information Retrieval
A novel efficient classification algorithm for search engines
AIC'08 Proceedings of the 8th conference on Applied informatics and communications
Exploring the efficacy of caption search for bioscience journal search interfaces
BioNLP '07 Proceedings of the Workshop on BioNLP 2007: Biological, Translational, and Clinical Language Processing
Figure classification in biomedical literature to elucidate disease mechanisms, based on pathways
Artificial Intelligence in Medicine
Invited paper: Structured literature image finder: Parsing text and figures in biomedical literature
Web Semantics: Science, Services and Agents on the World Wide Web
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
A new pivoting and iterative text detection algorithm for biomedical images
Journal of Biomedical Informatics
ISMB/ECCB'09 Proceedings of the 2009 workshop of the BioLink Special Interest Group, international conference on Linking Literature, Information, and Knowledge for Biology
ISMB/ECCB'09 Proceedings of the 2009 workshop of the BioLink Special Interest Group, international conference on Linking Literature, Information, and Knowledge for Biology
Automatic figure classification in bioscience literature
Journal of Biomedical Informatics
Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine
Figure Based Biomedical Document Retrieval System using Structural Image Features
International Journal of Knowledge Discovery in Bioinformatics
A novel figure panel classification and extraction method for document image understanding
International Journal of Data Mining and Bioinformatics
Hi-index | 3.84 |
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@cs.queensu.ca