ArticleJournal of biomedical informatics2012
A study of terminology auditors' performance for UMLS semantic type assignments.
Article in Journal of biomedical informatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Two complementary AI approaches for predicting UMLS semantic group assignment: heuristic reasoning and deep learning.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Mining of EHR for interface terminology concepts for annotating EHRs of COVID patients.BMC medical informatics and decision making · 2023Article
- A review of auditing techniques for the Unified Medical Language System.Journal of the American Medical Informatics Association : JAMIA · 2020Review
- Auditing the Assignments of Top-Level Semantic Types in the UMLS Semantic Network to UMLS Concepts.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2017Article
- A unified software framework for deriving, visualizing, and exploring abstraction networks for ontologies.Journal of biomedical informatics · 2016Article
- Utilizing a structural meta-ontology for family-based quality assurance of the BioPortal ontologies.Journal of biomedical informatics · 2016Article
- Quality Assurance of UMLS Semantic Type Assignments Using SNOMED CT Hierarchies.Methods of information in medicine · 2016Article
- A tribal abstraction network for SNOMED CT target hierarchies without attribute relationships.Journal of the American Medical Informatics Association : JAMIA · 2015Article
- Abstraction networks for terminologies: Supporting management of "big knowledge".Artificial intelligence in medicine · 2015Review
- Scalable quality assurance for large SNOMED CT hierarchies using subject-based subtaxonomies.Journal of the American Medical Informatics Association : JAMIA · 2015Article
- Sculpting the UMLS Refined Semantic Network.Online journal of public health informatics · 2014Article
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Authors and funding
9 authors.
Funding
Abstract
Auditing healthcare terminologies for errors requires human experts. In this paper, we present a study of the performance of auditors looking for errors in the semantic type assignments of complex UMLS concepts. In this study, concepts are considered complex whenever they are assigned combinations of semantic types. Past research has shown that complex concepts have a higher likelihood of errors. The results of this study indicate that individual auditors are not reliable when auditing such concepts and their performance is low, according to various metrics. These results confirm the outcomes of an earlier pilot study. They imply that to achieve an acceptable level of reliability and performance, when auditing such concepts of the UMLS, several auditors need to be assigned the same task. A mechanism is then needed to combine the possibly differing opinions of the different auditors into a final determination. In the current study, in contrast to our previous work, we used a majority mechanism for this purpose. For a sample of 232 complex UMLS concepts, the majority opinion was found reliable and its performance for accuracy, recall, precision and the F-measure was found statistically significantly higher than the average performance of individual auditors.
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