| Title |
Clot Analog Attenuation in Non-contrast CT Predicts Histology: an Experimental Study Using Machine Learning
|
|---|---|
| Published in |
Translational Stroke Research, January 2020
|
| DOI | 10.1007/s12975-019-00766-z |
| Pubmed ID | |
| Authors |
Aglae Velasco Gonzalez, Boris Buerke, Dennis Görlich, Manfred Fobker, Thilo Rusche, Cristina Sauerland, Norbert Meier, Astrid Jeibmann, Ray McCarthy, Harald Kugel, Peter Sporns, Andreas Faldum, Werner Paulus, Walter Heindel |
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 % |
|---|---|---|
| Netherlands | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 36 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 19% |
| Student > Bachelor | 4 | 11% |
| Student > Doctoral Student | 3 | 8% |
| Student > Ph. D. Student | 3 | 8% |
| Lecturer | 2 | 6% |
| Other | 4 | 11% |
| Unknown | 13 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 9 | 25% |
| Computer Science | 3 | 8% |
| Biochemistry, Genetics and Molecular Biology | 2 | 6% |
| Neuroscience | 2 | 6% |
| Engineering | 2 | 6% |
| Other | 3 | 8% |
| Unknown | 15 | 42% |
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 16 January 2020.
All research outputs
#20,599,981
of 23,186,937 outputs
Outputs from Translational Stroke Research
#363
of 447 outputs
Outputs of similar age
#381,990
of 456,833 outputs
Outputs of similar age from Translational Stroke Research
#17
of 18 outputs
Altmetric has tracked 23,186,937 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 447 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 1st percentile – i.e., 1% 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 456,833 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.