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Analysis of Uncertainty and Variability in Finite Element Computational Models for Biomedical Engineering: Characterization and Propagation

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, November 2016
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6 X users

Citations

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26 Dimensions

Readers on

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102 Mendeley
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Title
Analysis of Uncertainty and Variability in Finite Element Computational Models for Biomedical Engineering: Characterization and Propagation
Published in
Frontiers in Bioengineering and Biotechnology, November 2016
DOI 10.3389/fbioe.2016.00085
Pubmed ID
Authors

Nerea Mangado, Gemma Piella, Jérôme Noailly, Jordi Pons-Prats, Miguel Ángel González Ballester

Abstract

Computational modeling has become a powerful tool in biomedical engineering thanks to its potential to simulate coupled systems. However, real parameters are usually not accurately known, and variability is inherent in living organisms. To cope with this, probabilistic tools, statistical analysis and stochastic approaches have been used. This article aims to review the analysis of uncertainty and variability in the context of finite element modeling in biomedical engineering. Characterization techniques and propagation methods are presented, as well as examples of their applications in biomedical finite element simulations. Uncertainty propagation methods, both non-intrusive and intrusive, are described. Finally, pros and cons of the different approaches and their use in the scientific community are presented. This leads us to identify future directions for research and methodological development of uncertainty modeling in biomedical engineering.

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X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 2 2%
Unknown 100 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 19%
Student > Master 16 16%
Researcher 16 16%
Student > Bachelor 7 7%
Professor > Associate Professor 7 7%
Other 14 14%
Unknown 23 23%
Readers by discipline Count As %
Engineering 48 47%
Medicine and Dentistry 6 6%
Computer Science 5 5%
Neuroscience 3 3%
Biochemistry, Genetics and Molecular Biology 2 2%
Other 6 6%
Unknown 32 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 27 June 2019.
All research outputs
#12,777,062
of 22,899,952 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#1,342
of 6,653 outputs
Outputs of similar age
#152,597
of 312,379 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#3
of 23 outputs
Altmetric has tracked 22,899,952 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,653 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 79% 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 312,379 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.