Evidence map›Paper›PMID 25336590›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2015

Seeing the forest through the trees: uncovering phenomic complexity through interactive network visualization.

Jeremy L Warner, Joshua C Denny, David A Kreda, Gil Alterovitz

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
–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

13 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Applications of network analysis to routinely collected health care data: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2018
    Pooled it
  2. Pooled it
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  13. Visual analytics in healthcare--opportunities and research challenges.Journal of the American Medical Informatics Association : JAMIA · 2015
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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.

Jeremy L WarnerDivision of Hematology/Oncology, Department of Medicine, Vanderbilt University, Nashville, Tennessee, USA Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, USA.
Joshua C DennyDepartment of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, USA Division of General Internal Medicine, Department of Medicine, Vanderbilt University, Nashville, Tennessee, USA.
David A KredaCenter for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA.
Gil AlterovitzCenter for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA Children's Hospital Informatics Program at Harvard-MIT Division of Health Science, Boston, Massachusetts, USA Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.

Funding

From GWAS to PheWAS: Scanning the EMR Phenome for Gene-disease AssociationsR01LM010685 · NLM · VANDERBILT UNIVERSITY MEDICAL CENTER · PI BASTARACHE, LISA · 2011 to 2022
$6.3M
Automated Integration of Biomedical KnowledgeR01HG004836 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI ALTEROVITZ, GIL · 2009 to 2010
$856k
A Holistic Approach to Information Processing for Biomedical NetworksR00LM009826 · NLM · BOSTON CHILDREN'S HOSPITAL · PI ALTEROVITZ, GIL · 2010 to 2012
$727k
NHGRI NIH HHS 1R01HG004836-01NHGRI NIH HHS R01 HG004836NLM NIH HHS 4R00LM009826-03NLM NIH HHS R00 LM009826NLM NIH HHS R01 LM010685NLM NIH HHS R01LM010685
6 · The paper itself

Abstract

Our aim was to uncover unrecognized phenomic relationships using force-based network visualization methods, based on observed electronic medical record data. A primary phenotype was defined from actual patient profiles in the Multiparameter Intelligent Monitoring in Intensive Care II database. Network visualizations depicting primary relationships were compared to those incorporating secondary adjacencies. Interactivity was enabled through a phenotype visualization software concept: the Phenomics Advisor. Subendocardial infarction with cardiac arrest was demonstrated as a sample phenotype; there were 332 primarily adjacent diagnoses, with 5423 relationships. Primary network visualization suggested a treatment-related complication phenotype and several rare diagnoses; re-clustering by secondary relationships revealed an emergent cluster of smokers with the metabolic syndrome. Network visualization reveals phenotypic patterns that may have remained occult in pairwise correlation analysis. Visualization of complex data, potentially offered as point-of-care tools on mobile devices, may allow clinicians and researchers to quickly generate hypotheses and gain deeper understanding of patient subpopulations.

Indexed as

Audiovisual AidsData DisplayPattern Recognition, AutomatedUser-Computer InterfaceData displayData miningDecision making; computer-assistedMedical informatics applicationsPhenotype

Identifiers

PMID25336590
PMCPMC6080728

What OpenQuestion holds

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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.