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Attention Score in Context
Title |
Robustness to noise of arterial blood flow estimation methods in CT perfusion
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Published in |
BMC Research Notes, August 2014
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DOI | 10.1186/1756-0500-7-540 |
Pubmed ID | |
Authors |
Maria Romano, Michela D’Antò, Paolo Bifulco, Francesco Fiore, Mario Cesarelli |
Abstract |
Perfusion CT is a technology which allows functional evaluation of tissue vascularity. Due to this potential, it is finding increasing utility in oncology. Although since its introduction continuous advances have interested CT technique, some issues have to be still defined, concerning both clinical and technical aspects. In this study, we dealt with the comparison of two widely employed mathematical models (dual input one compartment model - DOCM - and maximum slope - SM -) analyzing their robustness to the noise. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Venezuela, Bolivarian Republic of | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 14 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 4 | 29% |
Researcher | 2 | 14% |
Professor | 2 | 14% |
Student > Master | 2 | 14% |
Other | 1 | 7% |
Other | 1 | 7% |
Unknown | 2 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 4 | 29% |
Engineering | 3 | 21% |
Nursing and Health Professions | 2 | 14% |
Computer Science | 1 | 7% |
Unknown | 4 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 18 August 2014.
All research outputs
#18,376,056
of 22,760,687 outputs
Outputs from BMC Research Notes
#3,013
of 4,262 outputs
Outputs of similar age
#167,569
of 235,035 outputs
Outputs of similar age from BMC Research Notes
#90
of 129 outputs
Altmetric has tracked 22,760,687 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,262 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 16th percentile – i.e., 16% of its peers scored the same or lower than it.
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 235,035 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 129 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.