ArticleJournal of the American Medical Informatics Association : JAMIA
Automated semantic indexing of figure captions to improve radiology image retrieval.
Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Extracting Semantics from Census-based Reference Data.Proceedings. IEEE International Conference on Semantic Computing · 2021Article
- Semantic-Enhanced Query Expansion System for Retrieving Medical Image Notes.Journal of medical systems · 2018Article
- Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features.Journal of Alzheimer's disease : JAD · 2017Article
- Imaging informatics: essential tools for the delivery of imaging services.Academic radiology · 2013Review
- Evaluating the Importance of Image-related Text for Ad-hoc and Case-based Biomedical Article Retrieval.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2010Article
- Improving image retrieval effectiveness via query expansion using MeSH hierarchical structure.Journal of the American Medical Informatics Association : JAMIAArticle
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Authors and funding
2 authors.
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Abstract
objectiveWe explored automated concept-based indexing of unstructured figure captions to improve retrieval of images from radiology journals.
designThe MetaMap Transfer program (MMTx) was used to map the text of 84,846 figure captions from 9,004 peer-reviewed, English-language articles to concepts in three controlled vocabularies from the UMLS Metathesaurus, version 2006AA. Sampling procedures were used to estimate the standard information-retrieval metrics of precision and recall, and to evaluate the degree to which concept-based retrieval improved image retrieval. MEASUREMENTS: Precision was estimated based on a sample of 250 concepts. Recall was estimated based on a sample of 40 concepts. The authors measured the impact of concept-based retrieval to improve upon keyword-based retrieval in a random sample of 10,000 search queries issued by users of a radiology image search engine.
resultsEstimated precision was 0.897 (95% confidence interval, 0.857-0.937). Estimated recall was 0.930 (95% confidence interval, 0.838-1.000). In 5,535 of 10,000 search queries (55%), concept-based retrieval found results not identified by simple keyword matching; in 2,086 searches (21%), more than 75% of the results were found by concept-based search alone.
conclusionConcept-based indexing of radiology journal figure captions achieved very high precision and recall, and significantly improved image retrieval.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.