Evidence map›Paper›PMID 23304293›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2012

New abstraction networks and a new visualization tool in support of auditing the SNOMED CT content.

James Geller, Christopher Ochs, Yehoshua Perl, Junchuan Xu

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Identifying Missing IS-A Relations in Orphanet Rare Disease Ontology.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2022
    Article
  2. Article
  3. Article
  4. Introducing the Big Knowledge to Use (BK2U) challenge.Annals of the New York Academy of Sciences · 2017
    Review
  5. Article
  6. Article
  7. Tracking the Remodeling of SNOMED CT's Bacterial Infectious Diseases.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016
    Article
  8. Article
  9. Scalable quality assurance for large SNOMED CT hierarchies using subject-based subtaxonomies.Journal of the American Medical Informatics Association : JAMIA · 2015
    Article
  10. A tribal abstraction network for SNOMED CT target hierarchies without attribute relationships.Journal of the American Medical Informatics Association : JAMIA · 2015
    Article
  11. Review
  12. An empirically derived taxonomy of errors in SNOMED CT.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2014
    Article
  13. Article
  14. Scalability of abstraction-network-based quality assurance to large SNOMED hierarchies.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2013
    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.

James GellerNew Jersey Institute of Technology, Newark, NJ, USA.
Christopher Ochs
Yehoshua Perl
Junchuan Xu

Funding

Taxonomies Supporting Orientation, Navigation and Auditing of TerminologiesR01LM008912 · NLM · NEW JERSEY INSTITUTE OF TECHNOLOGY · PI PERL, YEHOSHUA · 2007 to 2010
$929k
NLM NIH HHS R01 LM008912NLM NIH HHS R01 LM008912-S2
6 · The paper itself

Abstract

Medical terminologies are large and complex. Frequently, errors are hidden in this complexity. Our objective is to find such errors, which can be aided by deriving abstraction networks from a large terminology. Abstraction networks preserve important features but eliminate many minor details, which are often not useful for identifying errors. Providing visualizations for such abstraction networks aids auditors by allowing them to quickly focus on elements of interest within a terminology. Previously we introduced area taxonomies and partial area taxonomies for SNOMED CT. In this paper, two advanced, novel kinds of abstraction networks, the relationship-constrained partial area subtaxonomy and the root-constrained partial area subtaxonomy are defined and their benefits are demonstrated. We also describe BLUSNO, an innovative software tool for quickly generating and visualizing these SNOMED CT abstraction networks. BLUSNO is a dynamic, interactive system that provides quick access to well organized information about SNOMED CT.

Indexed as

Systematized Nomenclature of MedicineArtificial IntelligenceClassificationQuality Control

Identifiers

PMID23304293
PMCPMC3540556

What OpenQuestion holds

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Registered trials

None linked

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.