ArticleJournal of biomedical semantics2011
Logic-based assessment of the compatibility of UMLS ontology sources.
Article in Journal of biomedical semantics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- A semantic approach to mapping the Provenance Ontology to Basic Formal Ontology.Scientific data · 2025Article
- Impact of Translation on Biomedical Information Extraction: Experiment on Real-Life Clinical Notes.JMIR medical informatics · 2024Article
- Performance assessment of ontology matching systems for FAIR data.Journal of biomedical semantics · 2022Article
- Robust Knowledge Graph Completion with Stacked Convolutions and a Student Re-Ranking Network.Proceedings of the conference. Association for Computational Linguistics. Meeting · 2021Article
- Biomedical Vocabulary Alignment at Scale in the UMLS Metathesaurus.Proceedings of the ... International World-Wide Web Conference. International WWW Conference · 2021Article
- A review of auditing techniques for the Unified Medical Language System.Journal of the American Medical Informatics Association : JAMIA · 2020Review
- Biomedical ontology alignment: an approach based on representation learning.Journal of biomedical semantics · 2018Article
- Improving the interoperability of biomedical ontologies with compound alignments.Journal of biomedical semantics · 2018Article
- Matching disease and phenotype ontologies in the ontology alignment evaluation initiative.Journal of biomedical semantics · 2017Article
- Biomedical semantics in the Semantic Web.Journal of biomedical semantics · 2011Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe UMLS Metathesaurus (UMLS-Meta) is currently the most comprehensive effort for integrating independently-developed medical thesauri and ontologies. UMLS-Meta is being used in many applications, including PubMed and ClinicalTrials.gov. The integration of new sources combines automatic techniques, expert assessment, and auditing protocols. The automatic techniques currently in use, however, are mostly based on lexical algorithms and often disregard the semantics of the sources being integrated.
resultsIn this paper, we argue that UMLS-Meta's current design and auditing methodologies could be significantly enhanced by taking into account the logic-based semantics of the ontology sources. We provide empirical evidence suggesting that UMLS-Meta in its 2009AA version contains a significant number of errors; these errors become immediately apparent if the rich semantics of the ontology sources is taken into account, manifesting themselves as unintended logical consequences that follow from the ontology sources together with the information in UMLS-Meta. We then propose general principles and specific logic-based techniques to effectively detect and repair such errors.
conclusionsOur results suggest that the methodologies employed in the design of UMLS-Meta are not only very costly in terms of human effort, but also error-prone. The techniques presented here can be useful for both reducing human effort in the design and maintenance of UMLS-Meta and improving the quality of its contents.
Identifiers
What OpenQuestion holds
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.