Annotation of figures from the biomedical imaging literature: A comparative analysis of radlex and other standardized vocabularies

摘要

Rationale and Objectives: RadLex is a standardized vocabulary developed for clinical practice, research, and education in radiology. This report sought to analyze the use of RadLex to annotate and index the captions of images from the peer-reviewed biomedical literature and to compare the number of annotations per term for RadLex and five other biomedical ontologies in a large corpus of figure captions from biomedical imaging publications. Materials and Methods: RadLex and five other biomedical vocabularies were evaluated. A fully automated web service was used to discover the vocabularies' terms in a collection of 385,018 figure captions from 613 peer-reviewed biomedical journals. Annotations (i.e., figure-term pairs) were analyzed by vocabulary. RadLex annotations were analyzed by journal and RadLex term class. Results: RadLex had the greatest number of annotations per term of the six vocabularies. On average, there were 10.1 RadLex annotations per figure; 380,338 figures (98.8%) were annotated with at least one RadLex term and 288,163 figures (74.8%) were annotated with six or more RadLex terms. Of 39,218 RadLex terms, 8504 (21.7%) were mapped to images in the collection, which was the highest percentage of any of the vocabularies. Conclusions: Although comprising four to 10 times fewer terms than other vocabularies, RadLex showed excellent performance in indexing radiology-centric content. Almost all of the images in a large collection of figures from peer-reviewed biomedical journals were annotated with at least one RadLex term, and almost 75% of the images were annotated with six or more terms.