Evidence map›Paper›PMID 29854100›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2017

Quality Assurance of NCI Thesaurus by Mining Structural-Lexical Patterns.

Rashmie Abeysinghe, Michael A Brooks, Jeffery Talbert, Cui Licong

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
  2. 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 · 2024
    Article
  3. Identifying Missing IS-A Relations in Orphanet Rare Disease Ontology.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2022
    Article
  4. A substring replacement approach for identifying missing IS-A relations in SNOMED CT.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2022
    Article
  5. Article
  6. Article
  7. Leveraging non-lattice subgraphs for suggestion of new concepts for SNOMED CT.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2021
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Leveraging Non-lattice Subgraphs to Audit Hierarchical Relations in NCI Thesaurus.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2019
    Article
  14. Article
  15. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Rashmie AbeysingheDepartment of Computer Science, University of Kentucky, Lexington, KY.
Michael A BrooksDepartments of Radiology and Medicine, University of Kentucky, Lexington, KY.
Jeffery TalbertInstitute for Pharmaceutical Outcomes and Policy, University of Kentucky, Lexington, KY.
Cui LicongDepartment of Computer Science, University of Kentucky, Lexington, KY.

Funding

Kentucky Center for Clinical and Translational ScienceUL1TR001998 · NCATS · UNIVERSITY OF KENTUCKY · PI HARTMANN, KATHERINE E, KERN, PHILIP A · 2016 to 2025
$34.2M
NCATS NIH HHS UL1 TR001998
6 · The paper itself

Abstract

Quality assurance of biomedical terminologies such as the National Cancer Institute (NCI) Thesaurus is an essential part of the terminology management lifecycle. We investigate a structural-lexical approach based on non-lattice subgraphs to automatically identify missing hierarchical relations and missing concepts in the NCI Thesaurus. We mine six structural-lexical patterns exhibiting in non-lattice subgraphs: containment, union, intersection, union-intersection, inference-contradiction, and inference union. Each pattern indicates a potential specific type of error and suggests a potential type of remediation. We found 809 non-lattice subgraphs with these patterns in the NCI Thesaurus (version 16.12d). Domain experts evaluated a random sample of 50 small non-lattice subgraphs, of which 33 were confirmed to contain errors and make correct suggestions (33/50 = 66%). Of the 25 evaluated subgraphs revealing multiple patterns, 22 were verified correct (22/25 = 88%). This shows the effectiveness of our structurallexical-pattern-based approach in detecting errors and suggesting remediations in the NCI Thesaurus.

Indexed as

National Cancer Institute (U.S.)Vocabulary, ControlledData MiningQuality ControlSubject HeadingsUnited States

Identifiers

PMID29854100
PMCPMC5977579

What OpenQuestion holds

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Registered trials

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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.