| Title |
Radiomic Machine Learning for Characterization of Prostate Lesions with MRI: Comparison to ADC Values.
|
|---|---|
| Published in |
Radiology, July 2018
|
| DOI | 10.1148/radiol.2018173064 |
| Pubmed ID | |
| Authors |
David Bonekamp, Simon Kohl, Manuel Wiesenfarth, Patrick Schelb, Jan Philipp Radtke, Michael Götz, Philipp Kickingereder, Kaneschka Yaqubi, Bertram Hitthaler, Nils Gählert, Tristan Anselm Kuder, Fenja Deister, Martin Freitag, Markus Hohenfellner, Boris A Hadaschik, Heinz-Peter Schlemmer, Klaus H Maier-Hein |
X Demographics
The data shown below were collected from the profiles of 15 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 | 4 | 27% |
| Germany | 3 | 20% |
| Venezuela, Bolivarian Republic of | 1 | 7% |
| Portugal | 1 | 7% |
| Netherlands | 1 | 7% |
| Unknown | 5 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 47% |
| Practitioners (doctors, other healthcare professionals) | 3 | 20% |
| Scientists | 3 | 20% |
| Science communicators (journalists, bloggers, editors) | 2 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 202 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 202 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 31 | 15% |
| Researcher | 29 | 14% |
| Student > Master | 22 | 11% |
| Other | 16 | 8% |
| Student > Bachelor | 11 | 5% |
| Other | 32 | 16% |
| Unknown | 61 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 67 | 33% |
| Computer Science | 21 | 10% |
| Engineering | 14 | 7% |
| Biochemistry, Genetics and Molecular Biology | 3 | 1% |
| Physics and Astronomy | 3 | 1% |
| Other | 14 | 7% |
| Unknown | 80 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 09 November 2023.
All research outputs
#3,254,085
of 25,837,817 outputs
Outputs from Radiology
#2,064
of 10,427 outputs
Outputs of similar age
#60,934
of 343,321 outputs
Outputs of similar age from Radiology
#38
of 122 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,427 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.2. This one has done well, scoring higher than 79% 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 343,321 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 122 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 68% of its contemporaries.