ArticleSummit on translational bioinformatics2010
Evaluating the impact of conceptual knowledge engineering on the design and usability of a clinical and translational science collaboration portal.
Article in Summit on translational bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- Design and implementation of a randomized controlled trial of genomic counseling for patients with chronic disease.Journal of personalized medicine · 2014Article
- The TOKEn project: knowledge synthesis for in silico science.Journal of the American Medical Informatics Association : JAMIA · 2011Article
- Applying knowledge-anchored hypothesis discovery methods to advance clinical and translational research: the OAMiner project.Journal of the American Medical Informatics Association : JAMIAArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
With the growing prevalence of large-scale, team science endeavors in the biomedical and life science domains, the impetus to implement platforms capable of supporting asynchronous interaction among multidisciplinary groups of collaborators has increased commensurately. However, there is a paucity of literature describing systematic approaches to identifying the information needs of targeted end-users for such platforms, and the translation of such requirements into practicable software component design criteria. In previous studies, we have reported upon the efficacy of employing conceptual knowledge engineering (CKE) techniques to systematically address both of the preceding challenges in the context of complex biomedical applications. In this manuscript we evaluate the impact of CKE approaches relative to the design of a clinical and translational science collaboration portal, and report upon the preliminary qualitative users satisfaction as reported for the resulting system.
Identifiers
21347146PMC3041529What OpenQuestion holds
Registered trials
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.