Evidence map›Paper›PMID 29854206›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2017

Mining Hierarchies and Similarity Clusters from Value Set Repositories.

Kevin J Peterson, Guoqian Jiang, Scott M Brue, Feichen Shen, Hongfang Liu

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 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
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

5 authors.

Kevin J PetersonDivision of Information Management and Analytics, Mayo Clinic, Rochester, MN.
Guoqian JiangDepartment of Health Sciences Research, Mayo Clinic, Rochester, MN.
Scott M BrueDivision of Information Management and Analytics, Mayo Clinic, Rochester, MN.
Feichen ShenDepartment of Health Sciences Research, Mayo Clinic, Rochester, MN.
Hongfang LiuDepartment of Health Sciences Research, Mayo Clinic, Rochester, MN.

Funding

Tools for standardizing clinical research metadata using HL7 FHIRU01HG009450 · NHGRI · MAYO CLINIC ROCHESTER · PI JIANG, GUOQIAN · 2016 to 2018
$1.4M
caCDE-QA: A Quality Assurance Platform for Cancer Study Common Data ElementsU01CA180940 · NCI · MAYO CLINIC ROCHESTER · PI JIANG, GUOQIAN · 2014 to 2016
$1.1M
NCI NIH HHS U01 CA180940NHGRI NIH HHS U01 HG009450
6 · The paper itself

Abstract

A value set is a collection of permissible values used to describe a specific conceptual domain for a given purpose. By helping to establish a shared semantic understanding across use cases, these artifacts are important enablers of interoperability and data standardization. As the size of repositories cataloging these value sets expand, knowledge management challenges become more pronounced. Specifically, discovering value sets applicable to a given use case may be challenging in a large repository. In this study, we describe methods to extract implicit relationships between value sets, and utilize these relationships to overlay organizational structure onto value set repositories. We successfully extract two different structurings, hierarchy and clustering, and show how tooling can leverage these structures to enable more effective value set discovery.

Indexed as

Data MiningVocabulary, ControlledCluster AnalysisHealth Information InteroperabilitySemantics

Identifiers

PMID29854206
PMCPMC5977603

What OpenQuestion holds

Textmetadata
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.