Enhancing biomedical search interfaces with images.
Journal
Bioinformatics advances
ISSN: 2635-0041
Titre abrégé: Bioinform Adv
Pays: England
ID NLM: 9918282081306676
Informations de publication
Date de publication:
2023
2023
Historique:
received:
15
05
2023
revised:
30
06
2023
accepted:
14
07
2023
medline:
24
7
2023
pubmed:
24
7
2023
entrez:
24
7
2023
Statut:
epublish
Résumé
Figures in biomedical papers communicate essential information with the potential to identify relevant documents in biomedical and clinical settings. However, academic search interfaces mainly search over text fields. We describe a search system for biomedical documents that leverages image modalities and an existing index server. We integrate a problem-specific taxonomy of image modalities and image-based data into a custom search system. Our solution features a front-end interface to enhance classical document search results with image-related data, including page thumbnails, figures, captions and image-modality information. We demonstrate the system on a subset of the CORD-19 document collection. A quantitative evaluation demonstrates higher precision and recall for biomedical document retrieval. A qualitative evaluation with domain experts further highlights our solution's benefits to biomedical search. A demonstration is available at https://runachay.evl.uic.edu/scholar. Our code and image models can be accessed via github.com/uic-evl/bio-search. The dataset is continuously expanded.
Identifiants
pubmed: 37485423
doi: 10.1093/bioadv/vbad095
pii: vbad095
pmc: PMC10359625
doi:
Types de publication
Journal Article
Langues
eng
Pagination
vbad095Informations de copyright
© The Author(s) 2023. Published by Oxford University Press.
Déclaration de conflit d'intérêts
None declared.
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