Utilizing image and caption information for biomedical document classification

Pengyuan Li, Xiangying Jiang, Gongbo Zhang, Juan Trelles Trabucco, Daniela Raciti, Cynthia L. Smith, Martin Ringwald, G. Elisabeta Marai, Cecilia N. Arighi, Hagit Shatkay

Abstract: Biomedical research findings are typically disseminated through publications. To simplify access to domain-specific knowledge while supporting the research community, several biomedical databases devote significant effort to manual curation of the literature—a labor intensive process. The first step toward biocuration requires identifying articles relevant to the specific area on which the database focuses. Thus, automatically identifying publications relevant to a specific topic within a large volume of publications is an important task toward expediting the biocuration process and, in turn, biomedical research. Current methods focus on textual contents, typically extracted from the title-and-abstract. Notably, images and captions are often used in publications to convey pivotal evidence about processes, experiments and results.