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X Demographics
Mendeley readers
Attention Score in Context
| Title |
MITK-ModelFit: A generic open-source framework for model fits and their exploration in medical imaging – design, implementation and application on the example of DCE-MRI
|
|---|---|
| Published in |
BMC Bioinformatics, January 2019
|
| DOI | 10.1186/s12859-018-2588-1 |
| Pubmed ID | |
| Authors |
Charlotte Debus, Ralf Floca, Michael Ingrisch, Ina Kompan, Klaus Maier-Hein, Amir Abdollahi, Marco Nolden |
X Demographics
The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 4 | 44% |
| United States | 2 | 22% |
| United Kingdom | 1 | 11% |
| Unknown | 2 | 22% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 44% |
| Scientists | 3 | 33% |
| Practitioners (doctors, other healthcare professionals) | 2 | 22% |
Mendeley readers
The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 64 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 17% |
| Student > Master | 7 | 11% |
| Student > Bachelor | 6 | 9% |
| Student > Doctoral Student | 5 | 8% |
| Student > Ph. D. Student | 5 | 8% |
| Other | 9 | 14% |
| Unknown | 21 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 11 | 17% |
| Computer Science | 7 | 11% |
| Engineering | 5 | 8% |
| Neuroscience | 5 | 8% |
| Physics and Astronomy | 4 | 6% |
| Other | 7 | 11% |
| Unknown | 25 | 39% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 December 2020.
All research outputs
#5,932,028
of 23,881,329 outputs
Outputs from BMC Bioinformatics
#2,097
of 7,454 outputs
Outputs of similar age
#119,130
of 442,487 outputs
Outputs of similar age from BMC Bioinformatics
#54
of 192 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,454 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 71% 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 442,487 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 73% of its contemporaries.
We're also able to compare this research output to 192 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.