Evidence map›Paper›PMID 26167381›Full record

ArticleJournal of pathology informatics2015

Biomedical imaging ontologies: A survey and proposal for future work.

Barry Smith, Sivaram Arabandi, Mathias Brochhausen, Michael Calhoun, Paolo Ciccarese, Scott Doyle, Bernard Gibaud, Ilya Goldberg, Charles E Kahn, James Overton and 2 more

Abstract read
In one paragraph

Article in Journal of pathology informatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Population health management fit lifecycles in analytics.Frontiers in artificial intelligence · 2025
    Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Artificial intelligence driven next-generation renal histomorphometry.Current opinion in nephrology and hypertension · 2020
    Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Imaging Informatics: 25 Years of Progress.Yearbook of medical informatics · 2016
    Article
  15. 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

12 authors.

Barry SmithDepartment of Philosophy, The State University of New York at Buffalo, Buffalo, NY 14260, USA.
Sivaram ArabandiOntopro LLC, Houston, TX 77025, USA.
Mathias BrochhausenDivision of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA.
Michael CalhounDepartment of Health and Human Performance, Elon University, Elon, NC 27244, USA.
Paolo CiccareseHarvard Medical School, Massachusetts General Hospital, PerkinElmer Innovation Labs, Boston, MA 02115, USA.
Scott DoyleDepartment of Pathology and Anatomical Sciences, University at Buffalo, The State University of New York, Buffalo, NY 14214, USA.
Bernard GibaudLaboratoire du Traitement du Signal et de l'Image (LTSI), Inserm Unit 1099, University of Rennes 1, Rennes, France.
Ilya GoldbergNational Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
Charles E KahnDepartment of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA.
James OvertonKnocean, Toronto, Ontario, M6P 2T3, Canada.
John TomaszewskiDepartment of Pathology and Anatomical Sciences, University at Buffalo, The State University of New York, Buffalo, NY 14214, USA.
Metin GurcanDepartment of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA.

Funding

Computer-based assessment of tumor microenvironment (TME) in Follicular LymphomaR01CA134451 · NCI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI GURCAN, METIN NAFI, LOZANSKI, GERARD · 2009 to 2017
$2.3M
Development And Applications Of The Open Microscopy Environment (OME)ZIAAG000671 · NIA · NATIONAL INSTITUTE ON AGING · PI GOLDBERG, ILYA · 2012 to 2016
$1.8M
Mesenchynmal stem cells as a protective niche for latent M. tuberculosisR56AI111823 · NIAID · ADA FORSYTH INSTITUTE, INC. · PI BEAMER, GILLIAN L, CAMPOS-NETO, ANTONIO · 2014 to 2014
$619k
Development/Applications Of Open Microscopy EnvironmentZ01AG000671 · NIA · NATIONAL INSTITUTE ON AGING · PI GOLDBERG, ILYA · 2002 to 2008
$483k
Intramural NIH HHS Z01 AG000671NCI NIH HHS R01 CA134451NIAID NIH HHS R56 AI111823
6 · The paper itself

Abstract

backgroundOntology is one strategy for promoting interoperability of heterogeneous data through consistent tagging. An ontology is a controlled structured vocabulary consisting of general terms (such as "cell" or "image" or "tissue" or "microscope") that form the basis for such tagging. These terms are designed to represent the types of entities in the domain of reality that the ontology has been devised to capture; the terms are provided with logical definitions thereby also supporting reasoning over the tagged data.

aimThis paper provides a survey of the biomedical imaging ontologies that have been developed thus far. It outlines the challenges, particularly faced by ontologies in the fields of histopathological imaging and image analysis, and suggests a strategy for addressing these challenges in the example domain of quantitative histopathology imaging. RESULTS AND

conclusionsThe ultimate goal is to support the multiscale understanding of disease that comes from using interoperable ontologies to integrate imaging data with clinical and genomics data.

Indexed as

Histopathology imaginginteroperabilityontologyquantitative histopathology image ontology

Identifiers

PMID26167381
PMCPMC4485195

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.