ArticleJournal of biomedical semantics2022
Identification of missing hierarchical relations in the vaccine ontology using acquired term pairs.
Article in Journal of biomedical semantics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- VO: The Vaccine Ontology.Scientific data · 2026Article
- VO: The Vaccine Ontology.bioRxiv : the preprint server for biology · 2025Article
- Leveraging logical definitions and lexical features to detect missing IS-A relations in biomedical terminologies.Journal of biomedical semantics · 2024Article
- An Automated Approach for Identifying Erroneous IS-A Relations in SNOMED CT.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024Article
- Identifying Missing IS-A Relations in Orphanet Rare Disease Ontology.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
backgroundThe Vaccine Ontology (VO) is a biomedical ontology that standardizes vaccine annotation. Errors in VO will affect a multitude of applications that it is being used in. Quality assurance of VO is imperative to ensure that it provides accurate domain knowledge to these downstream tasks. Manual review to identify and fix quality issues (such as missing hierarchical is-a relations) is challenging given the complexity of the ontology. Automated approaches are highly desirable to facilitate the quality assurance of VO.
methodsWe developed an automated lexical approach that identifies potentially missing is-a relations in VO. First, we construct two types of VO concept-pairs: (1) linked; and (2) unlinked. Each concept-pair further derives an Acquired Term Pair (ATP) based on their lexical features. If the same ATP is obtained by a linked concept-pair and an unlinked concept-pair, this is considered to indicate a potentially missing is-a relation between the unlinked pair of concepts.
resultsApplying this approach on the 1.1.192 version of VO, we were able to identify 232 potentially missing is-a relations. A manual review by a VO domain expert on a random sample of 70 potentially missing is-a relations revealed that 65 of the cases were valid missing is-a relations in VO (a precision of 92.86%).
conclusionsThe results indicate that our approach is highly effective in identifying missing is-a relation in VO.
Indexed as
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.