Evidence map›Paper›PMID 28725879›Full record

Article... IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics2017

Using Closure Tables to Enable Cross-Querying of Ontologies in Database-Driven Applications.

Daniel R Harris, Darren W Henderson, Jeffery C Talbert

Abstract read
In one paragraph

Article in ... IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Daniel R HarrisCenter for Clinical and Translational Sciences, University of Kentucky, Lexington, Kentucky 40506.
Darren W HendersonCenter for Clinical and Translational Sciences, University of Kentucky, Lexington, Kentucky 40506.
Jeffery C TalbertCenter for Clinical and Translational Sciences, University of Kentucky, Lexington, Kentucky 40506.

Funding

Kentucky Center for Clinical and Translational ScienceUL1TR001998 · NCATS · UNIVERSITY OF KENTUCKY · PI HARTMANN, KATHERINE E, KERN, PHILIP A · 2016 to 2025
$34.2M
Kentucky Center for Clinical and Translational ScienceUL1TR000117 · NCATS · UNIVERSITY OF KENTUCKY · PI KERN, PHILIP A · 2012 to 2015
$13.3M
NCATS NIH HHS UL1 TR000117NCATS NIH HHS UL1 TR001998
6 · The paper itself

Abstract

We demonstrate that closure tables are an effective data structure for developing database-driven applications that query biomedical ontologies and that require cross-querying between multiple ontologies. A closure table stores all available paths within a tree, even those without a direct parent-child relationship; additionally, a node can have multiple ancestors which gives the foundation for supporting linkages between controlled ontologies. We augment the meta-data structure of the ICD9 and ICD10 ontologies included in i2b2, an open source query tool for identifying patient cohorts, to utilize a closure table. We describe our experiences in incorporating existing mappings between ontologies to enable clinical and health researchers to identify patient populations using the ontology that best matches their preference and expertise.

Identifiers

PMID28725879
PMCPMC5512279

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.