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Ensuring reliability of safety-critical clinical applications of computational cardiac models

Overview of attention for article published in Frontiers in Physiology, January 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

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1 policy source
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4 X users
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1 YouTube creator

Citations

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45 Dimensions

Readers on

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49 Mendeley
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1 CiteULike
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Title
Ensuring reliability of safety-critical clinical applications of computational cardiac models
Published in
Frontiers in Physiology, January 2013
DOI 10.3389/fphys.2013.00358
Pubmed ID
Authors

Pras Pathmanathan, Richard A. Gray

Abstract

Computational models of cardiac electrophysiology have been used for over half a century to investigate physiological mechanisms and generate hypotheses for experimental testing, and are now starting to play a role in clinical applications. There is currently a great deal of interest in using models as diagnostic or therapeutic aids, for example using patient-specific whole-heart simulations to optimize cardiac resynchronization therapy, ablation therapy, and defibrillation. However, if models are to be used in safety-critical clinical decision making, the reliability of their predictions needs to be thoroughly investigated. In engineering and the physical sciences, the field of "verification, validation and uncertainty quantification" (VVUQ) [also known as "verification and validation" (V&V)] has been developed for rigorously evaluating the credibility of computational model predictions. In this article we first discuss why it is vital that cardiac models be developed and evaluated within a VVUQ framework, and then consider cardiac models in the context of each of the stages in VVUQ. We identify some of the major difficulties which may need to be overcome for cardiac models to be used in safely-critical clinical applications.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 6%
Chile 1 2%
Spain 1 2%
Italy 1 2%
Unknown 43 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 27%
Student > Ph. D. Student 10 20%
Professor > Associate Professor 3 6%
Professor 3 6%
Student > Bachelor 3 6%
Other 11 22%
Unknown 6 12%
Readers by discipline Count As %
Engineering 16 33%
Mathematics 5 10%
Computer Science 4 8%
Biochemistry, Genetics and Molecular Biology 3 6%
Agricultural and Biological Sciences 2 4%
Other 10 20%
Unknown 9 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 September 2020.
All research outputs
#5,400,655
of 22,736,112 outputs
Outputs from Frontiers in Physiology
#2,423
of 13,539 outputs
Outputs of similar age
#56,452
of 280,808 outputs
Outputs of similar age from Frontiers in Physiology
#83
of 398 outputs
Altmetric has tracked 22,736,112 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,539 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.5. This one has done well, scoring higher than 82% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 280,808 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 398 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.