title: Towards answering biological questions with experimental evidence: automatically identifying text that summarize image content in full-text articles.
abstract: Images (i.e., figures) are important experimental evidence that are typically reported in bioscience full-text articles. Biologists need to access images to validate research facts and to formulate or to test novel research hypotheses. We propose to build a biological question answering system that provides experimental evidences as answers in response to biological questions. As a first step, we develop natural language processing techniques to identify sentences that summarize image content.
authors.affiliation: Department of Health Sciences, University of Wisconsin-Milwaukee, USA.
authors.forename: Hong
authors.initials: H
authors.lastname: Yu
mesh_terms: D000465:Algorithms; D001690:Biological Science Disciplines; D016247:Information Storage and Retrieval / Q000379:methods*; D008488:Medical Illustration; D009323:Natural Language Processing