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Attention Score in Context
Title |
Accurate state estimation from uncertain data and models: an application of data assimilation to mathematical models of human brain tumors
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Published in |
Biology Direct, January 2011
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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. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 20% |
United Kingdom | 1 | 20% |
France | 1 | 20% |
Switzerland | 1 | 20% |
Unknown | 1 | 20% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 40% |
Scientists | 2 | 40% |
Practitioners (doctors, other healthcare professionals) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 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 | 39 | 89% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 9 | 20% |
Student > Master | 8 | 18% |
Researcher | 6 | 14% |
Student > Bachelor | 6 | 14% |
Student > Doctoral Student | 4 | 9% |
Other | 2 | 5% |
Unknown | 9 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 7 | 16% |
Engineering | 6 | 14% |
Physics and Astronomy | 4 | 9% |
Medicine and Dentistry | 4 | 9% |
Mathematics | 4 | 9% |
Other | 8 | 18% |
Unknown | 11 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 23. 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 October 2023.
All research outputs
#1,566,351
of 24,682,395 outputs
Outputs from Biology Direct
#47
of 523 outputs
Outputs of similar age
#8,364
of 190,793 outputs
Outputs of similar age from Biology Direct
#7
of 27 outputs
Altmetric has tracked 24,682,395 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 523 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.4. This one has done particularly well, scoring higher than 91% 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 190,793 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 27 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.