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Can SNOMED CT be squeezed without losing its shape?

Overview of attention for article published in Journal of Biomedical Semantics, January 2016
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Title
Can SNOMED CT be squeezed without losing its shape?
Published in
Journal of Biomedical Semantics, January 2016
DOI 10.1186/s13326-016-0101-1
Pubmed ID
Authors

Pablo López-García, Stefan Schulz

Abstract

In biomedical applications where the size and complexity of SNOMED CT become problematic, using a smaller subset that can act as a reasonable substitute is usually preferred. In a special class of use cases-like ontology-based quality assurance, or when performing scaling experiments for real-time performance-it is essential that modules show a similar shape than SNOMED CT in terms of concept distribution per sub-hierarchy. Exactly how to extract such balanced modules remains unclear, as most previous work on ontology modularization has focused on other problems. In this study, we investigate to what extent extracting balanced modules that preserve the original shape of SNOMED CT is possible, by presenting and evaluating an iterative algorithm. We used a graph-traversal modularization approach based on an input signature. To conform to our definition of a balanced module, we implemented an iterative algorithm that carefully bootstraped and dynamically adjusted the signature at each step. We measured the error for each sub-hierarchy and defined convergence as a residual sum of squares <1. Using 2000 concepts as an initial signature, our algorithm converged after seven iterations and extracted a module 4.7 % the size of SNOMED CT. Seven sub-hierarhies were either over or under-represented within a range of 1-8 %. Our study shows that balanced modules from large terminologies can be extracted using ontology graph-traversal modularization techniques under certain conditions: that the process is repeated a number of times, the input signature is dynamically adjusted in each iteration, and a moderate under/over-representation of some hierarchies is tolerated. In the case of SNOMED CT, our results conclusively show that it can be squeezed to less than 5 % of its size without any sub-hierarchy losing its shape more than 8 %, which is likely sufficient in most use cases.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 5 24%
Student > Master 5 24%
Researcher 3 14%
Student > Bachelor 2 10%
Student > Doctoral Student 1 5%
Other 4 19%
Unknown 1 5%
Readers by discipline Count As %
Medicine and Dentistry 7 33%
Unspecified 5 24%
Computer Science 5 24%
Biochemistry, Genetics and Molecular Biology 1 5%
Nursing and Health Professions 1 5%
Other 0 0%
Unknown 2 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 November 2016.
All research outputs
#11,565,937
of 17,800,904 outputs
Outputs from Journal of Biomedical Semantics
#216
of 339 outputs
Outputs of similar age
#160,357
of 276,675 outputs
Outputs of similar age from Journal of Biomedical Semantics
#3
of 3 outputs
Altmetric has tracked 17,800,904 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 339 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
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We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.