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Accurate state estimation from uncertain data and models: an application of data assimilation to mathematical models of human brain tumors

Overview of attention for article published in Biology Direct, January 2011
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#50 of 469)
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
5 tweeters
googleplus
1 Google+ user

Citations

dimensions_citation
29 Dimensions

Readers on

mendeley
41 Mendeley
citeulike
1 CiteULike
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Title
Accurate state estimation from uncertain data and models: an application of data assimilation to mathematical models of human brain tumors
Published in
Biology Direct, January 2011
DOI 10.1186/1745-6150-6-64
Pubmed ID
Authors

Eric J Kostelich, Yang Kuang, Joshua M McDaniel, Nina Z Moore, Nikolay L Martirosyan, Mark C Preul

Abstract

Data assimilation refers to methods for updating the state vector (initial condition) of a complex spatiotemporal model (such as a numerical weather model) by combining new observations with one or more prior forecasts. We consider the potential feasibility of this approach for making short-term (60-day) forecasts of the growth and spread of a malignant brain cancer (glioblastoma multiforme) in individual patient cases, where the observations are synthetic magnetic resonance images of a hypothetical tumor.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 7%
Colombia 1 2%
Brazil 1 2%
Unknown 36 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 20%
Student > Master 8 20%
Researcher 6 15%
Student > Bachelor 6 15%
Student > Doctoral Student 4 10%
Other 3 7%
Unknown 6 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 17%
Engineering 6 15%
Medicine and Dentistry 4 10%
Mathematics 4 10%
Physics and Astronomy 3 7%
Other 9 22%
Unknown 8 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 21. 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 05 January 2012.
All research outputs
#1,398,887
of 21,542,809 outputs
Outputs from Biology Direct
#50
of 469 outputs
Outputs of similar age
#11,726
of 251,141 outputs
Outputs of similar age from Biology Direct
#7
of 30 outputs
Altmetric has tracked 21,542,809 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 469 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one has done well, scoring higher than 89% 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 251,141 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.