Evidence map›Paper›PMID 28215561›Full record

ArticleJournal of biomedical informatics2017

Analyzing structural changes in SNOMED CT's Bacterial infectious diseases using a visual semantic delta.

Christopher Ochs, James T Case, Yehoshua Perl

Abstract read
In one paragraph

Article in Journal of biomedical informatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Big knowledge visualization of the COVID-19 CIDO ontology evolution.BMC medical informatics and decision making · 2023
    Article
  2. Article
  3. Article
  4. 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

3 authors.

Christopher OchsComputer Science Department, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA. Electronic address: cro3@njit.edu.
James T CaseNational Library of Medicine/National Institutes of Health, Bethesda, MD 20894, USA.
Yehoshua PerlComputer Science Department, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA.

Funding

National Biomedical Information ServicesZIHLM200888 · NLM · NATIONAL LIBRARY OF MEDICINE · PI PALTOO, DINA · 2009 to 2025
$5200.7M
A family-based framework of quality assurance for biomedical ontologiesR01CA190779 · NCI · NEW JERSEY INSTITUTE OF TECHNOLOGY · PI PERL, YEHOSHUA · 2015 to 2017
$1.8M
NCI NIH HHS R01 CA190779
6 · The paper itself

Abstract

Thousands of changes are applied to SNOMED CT's concepts during each release cycle. These changes are the result of efforts to improve or expand the coverage of health domains in the terminology. Understanding which concepts changed, how they changed, and the overall impact of a set of changes is important for editors and end users. Each SNOMED CT release comes with delta files, which identify all of the individual additions and removals of concepts and relationships. These files typically contain tens of thousands of individual entries, overwhelming users. They also do not identify the editorial processes that were applied to individual concepts and they do not capture the overall impact of a set of changes on a subhierarchy of concepts. In this paper we introduce a methodology and accompanying software tool called a SNOMED CT Visual Semantic Delta ("semantic delta" for short) to enable a comprehensive review of changes in SNOMED CT. The semantic delta displays a graphical list of editing operations that provides semantics and context to the additions and removals in the delta files. However, there may still be thousands of editing operations applied to a set of concepts. To address this issue, a semantic delta includes a visual summary of changes that affected sets of structurally and semantically similar concepts. The software tool for creating semantic deltas offers views of various granularities, allowing a user to control how much change information they view. In this tool a user can select a set of structurally and semantically similar concepts and review the editing operations that affected their modeling. The semantic delta methodology is demonstrated on SNOMED CT's Bacterial infectious disease subhierarchy, which has undergone a significant remodeling effort over the last two years.

Indexed as

Bacterial InfectionsSemanticsSystematized Nomenclature of MedicineAlgorithmsHumansSoftwareSemantic deltaSNOMED CTTerminology change analysisTerminology change summaryTerminology diffTerminology evolution

Identifiers

PMID28215561
PMCPMC5407457

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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.