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Attention Score in Context
Title |
Improved operator agreement and efficiency using the minimum area contour change method for delineation of hyperintense multiple sclerosis lesions on FLAIR MRI
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Published in |
BMC Medical Imaging, September 2013
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DOI | 10.1186/1471-2342-13-29 |
Pubmed ID | |
Authors |
David S Wack, Michael G Dwyer, Niels Bergsland, Deepa Ramasamy, Carol Di Perri, Laura Ranza, Sara Hussein, Christopher Magnano, Kevin Seals, Robert Zivadinov |
Abstract |
Activity of disease in patients with multiple sclerosis (MS) is monitored by detecting and delineating hyper-intense lesions on MRI scans. The Minimum Area Contour Change (MACC) algorithm has been created with two main goals: a) to improve inter-operator agreement on outlining regions of interest (ROIs) and b) to automatically propagate longitudinal ROIs from the baseline scan to a follow-up scan. |
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 % |
---|---|---|
Spain | 1 | 20% |
Brazil | 1 | 20% |
United States | 1 | 20% |
Mexico | 1 | 20% |
Unknown | 1 | 20% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 4 | 80% |
Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 16 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Professor > Associate Professor | 3 | 19% |
Other | 3 | 19% |
Student > Ph. D. Student | 2 | 13% |
Student > Master | 2 | 13% |
Librarian | 1 | 6% |
Other | 0 | 0% |
Unknown | 5 | 31% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 5 | 31% |
Neuroscience | 2 | 13% |
Psychology | 1 | 6% |
Agricultural and Biological Sciences | 1 | 6% |
Computer Science | 1 | 6% |
Other | 1 | 6% |
Unknown | 5 | 31% |
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 14 October 2015.
All research outputs
#12,688,753
of 22,719,618 outputs
Outputs from BMC Medical Imaging
#124
of 589 outputs
Outputs of similar age
#97,196
of 196,897 outputs
Outputs of similar age from BMC Medical Imaging
#3
of 13 outputs
Altmetric has tracked 22,719,618 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 589 research outputs from this source. They receive a mean Attention Score of 2.1. This one has done well, scoring higher than 78% 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 196,897 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 13 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.