Anticipating annotations and emerging trends in biomedical literature

The BioJournalMonitor is a decision support system for the analysis of trends and topics in the biomedical literature. Its main goal is to identify potential diagnostic and therapeutic biomarkers for specific diseases. Several data sources are continuously integrated to provide the user with up-to-date information on current research in this field. State-of-theart text mining technologies are deployed to provide added value on top of the original content, including named entity detection, relation extraction, classification, clustering, ranking, summarization, and visualization. We present two novel technologies that are related to the analysis of temporal dynamics of text archives and associated ontologies. Currently, the MeSH ontology is used to annotate the scientific articles entering the PubMed database with medical terms. Both the maintenance of the ontology as well as the annotation of new articles is performed largely manually. We describe how probabilistic topic models can be...

• Type: Conference
• Year: 2008
• Where: KDD
• Authors: Bernd Wachmann, Dmitriy Fradkin, Fabian Mörchen, Julien Etienne, Markus Bundschus, Mathäus Dejori
• Keywords: Data Mining, KDD 2008, Likely Mesh Terms, MeSH Ontology, Miscellaneous General Terms