Exploring two biomedical text genres for disease recognition

In the framework of contextual information retrieval in the biomedical domain, this paper reports on the automatic detection of disease concepts in two genres of biomedical text: sentences from the literature and PubMed user queries. A statistical model and a Natural Language Processing algorithm for disease recognition were applied on both corpora. While both methods show good performance (F=77% vs. F=76%) on the sentence corpus, results on the query corpus indicate that the statistical model is more robust (F=74% vs. F=70%).