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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Automatic classification of dopamine transporter SPECT: deep convolutional neural networks can be trained to be robust with respect to variable image characteristics
|
|---|---|
| Published in |
European Journal of Nuclear Medicine and Molecular Imaging, August 2019
|
| DOI | 10.1007/s00259-019-04502-5 |
| Pubmed ID | |
| Authors |
Markus Wenzel, Fausto Milletari, Julia Krüger, Catharina Lange, Michael Schenk, Ivayla Apostolova, Susanne Klutmann, Marcus Ehrenburg, Ralph Buchert |
X Demographics
The data shown below were collected from the profiles of 6 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 | 2 | 33% |
| United Kingdom | 1 | 17% |
| Netherlands | 1 | 17% |
| Unknown | 2 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 50% |
| Scientists | 1 | 17% |
| Science communicators (journalists, bloggers, editors) | 1 | 17% |
| Practitioners (doctors, other healthcare professionals) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 66 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 20% |
| Researcher | 9 | 14% |
| Other | 6 | 9% |
| Student > Postgraduate | 6 | 9% |
| Student > Bachelor | 5 | 8% |
| Other | 10 | 15% |
| Unknown | 17 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 18 | 27% |
| Computer Science | 8 | 12% |
| Engineering | 6 | 9% |
| Neuroscience | 4 | 6% |
| Psychology | 2 | 3% |
| Other | 6 | 9% |
| Unknown | 22 | 33% |
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 28 November 2019.
All research outputs
#7,850,857
of 23,806,312 outputs
Outputs from European Journal of Nuclear Medicine and Molecular Imaging
#981
of 3,083 outputs
Outputs of similar age
#135,169
of 342,488 outputs
Outputs of similar age from European Journal of Nuclear Medicine and Molecular Imaging
#25
of 65 outputs
Altmetric has tracked 23,806,312 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,083 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one is in the 48th percentile – i.e., 48% 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 342,488 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 55% of its contemporaries.
We're also able to compare this research output to 65 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 58% of its contemporaries.