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Combining Text and Visual Features for Biomedical Information Retrieval and Ontologies.
The search for relevant and actionable information is key to achieving clinical and research goals in biomedicine. Biomedical information exists in different forms: as text and illustrations in journal articles and other documents, in 'images' stored in databases, and as patients' cases in electronic health records. Our objectives in this project may be formulated as seeking better ways to retrieve information from these entities, by moving beyond conventional text-based searching to combining both text and visual features in search queries. The approaches to meeting these objectives use a combination of techniques and tools from the fields of Information Retrieval (IR), Content-Based Image Retrieval (CBIR), and Natural Language Processing (NLP).