Publicación: Shangri–La: A medical case–based retrieval tool
Fecha
2018-11-28
Editor/a
Director/a
Tutor/a
Coordinador/a
Prologuista
Revisor/a
Ilustrador/a
Derechos de acceso
info:eu-repo/semantics/openAccess
Título de la revista
ISSN de la revista
Título del volumen
Editor
Wiley
Resumen
Large amounts of medical visual data are produced in hospitals daily and made available continuously via publications in the scientific literature, representing the medical knowledge. However, it is not always easy to find the desired information and in clinical routine the time to fulfil an information need is often very limited. Information retrieval systems are a useful tool to provide access to these documents/images in the biomedical literature related to information needs of medical professionals. Shangri–La is a medical retrieval system that can potentially help clinicians to make decisions on difficult cases. It retrieves articles from the biomedical literature when querying a case description and attached images. The system is based on a multimodal retrieval approach with a focus on the integration of visual information connected to text. The approach includes a query–adaptive multimodal fusion criterion that analyses if visual features are suitable to be fused with text for the retrieval. Furthermore, image modality information is integrated in the retrieval step. The approach is evaluated using the ImageCLEFmed 2013 medical retrieval benchmark and can thus be compared to other approaches. Results show that the final approach outperforms the best multimodal approach submitted to ImageCLEFmed 2013.
Descripción
Esta es la versión aceptada del artículo. La versión registrada fue publicada por primera vez en Journal of the Association for Information Science and Technology 68, n.º 11 (2017): 2587-2601, está disponible en línea en el sitio web del editor: Wiley, https://doi.org/10.1002/asi.23858.
This is the accepted version of the article. The registered version was first published in Journal of the Association for Information Science and Technology 68, no. 11 (2017): 2587-2601, is available online at the publisher's website: Wiley, https://doi.org/10.1002/asi.23858.
Categorías UNESCO
Palabras clave
Medical visual information retrieval, ImageCLEF, Medical case retrieval, Query adaptive multi–modal fusion, Shangri–La, Classification
Citación
Alba García Seco de Herrera, Roger Schaer, y Henning Müller. «Shangri–La: A medical case–based retrieval tool». Journal of the Association for Information Science and Technology 68, n.º 11 (2017): 2587-2601. https://doi.org/10.1002/ASI.23858.
Centro
E.T.S. de Ingeniería Informática
Departamento
Lenguajes y Sistemas Informáticos