Evidence map›Paper›PMID 18040742›Full record

ArticleJournal of digital imaging2009

A knowledge-anchored integrative image search and retrieval system.

Selnur Erdal, Umit V Catalyurek, Philip R O Payne, Joel Saltz, Jyoti Kamal, Metin N Gurcan

Abstract read
In one paragraph

Article in Journal of digital imaging, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

6 authors.

Selnur ErdalInformation Warehouse, The Ohio State University Medical Center, 640 Ackerman Road, P.O. Box 183111, Columbus, OH 43218, USA. selnur.erdal@osumc.edu
Umit V Catalyurek
Philip R O Payne
Joel Saltz
Jyoti Kamal
Metin N Gurcan

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical data that may be used in a secondary capacity to support research activities are regularly stored in three significantly different formats: (1) structured, codified data elements; (2) semi-structured or unstructured narrative text; and (3) multi-modal images. In this manuscript, we will describe the design of a computational system that is intended to support the ontology-anchored query and integration of such data types from multiple source systems. Additional features of the described system include (1) the use of Grid services-based electronic data interchange models to enable the use of our system in multi-site settings and (2) the use of a software framework intended to address both potential security and patient confidentiality concerns that arise when transmitting or otherwise manipulating potentially privileged personal health information. We will frame our discussion within the specific experimental context of the concept-oriented query and integration of correlated structured data, narrative text, and images for cancer research.

Indexed as

Medical Records Systems, ComputerizedRadiology Information SystemsSystems IntegrationUser-Computer InterfaceDatabases, FactualHumansInformation Storage and RetrievalSoftware

Identifiers

PMID18040742
PMCPMC3043680

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.