| Title |
Comparison of Artificial Intelligence Techniques to Evaluate Performance of a Classifier for Automatic Grading of Prostate Cancer From Digitized Histopathologic Images
|
|---|---|
| Published in |
JAMA Network Open, March 2019
|
| DOI | 10.1001/jamanetworkopen.2019.0442 |
| Pubmed ID | |
| Authors |
Guy Nir, Davood Karimi, S. Larry Goldenberg, Ladan Fazli, Brian F. Skinnider, Peyman Tavassoli, Dmitry Turbin, Carlos F. Villamil, Gang Wang, Darby J. S. Thompson, Peter C. Black, Septimiu E. Salcudean |
X Demographics
The data shown below were collected from the profiles of 19 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 | 7 | 37% |
| Canada | 4 | 21% |
| Comoros | 1 | 5% |
| Unknown | 7 | 37% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 12 | 63% |
| Scientists | 4 | 21% |
| Practitioners (doctors, other healthcare professionals) | 3 | 16% |
Mendeley readers
The data shown below were compiled from readership statistics for 133 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 133 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 20 | 15% |
| Researcher | 19 | 14% |
| Student > Ph. D. Student | 10 | 8% |
| Student > Bachelor | 9 | 7% |
| Student > Doctoral Student | 8 | 6% |
| Other | 19 | 14% |
| Unknown | 48 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 28 | 21% |
| Computer Science | 16 | 12% |
| Engineering | 9 | 7% |
| Biochemistry, Genetics and Molecular Biology | 6 | 5% |
| Agricultural and Biological Sciences | 4 | 3% |
| Other | 16 | 12% |
| Unknown | 54 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 25 January 2020.
All research outputs
#2,618,639
of 24,837,702 outputs
Outputs from JAMA Network Open
#6,645
of 9,012 outputs
Outputs of similar age
#57,125
of 357,795 outputs
Outputs of similar age from JAMA Network Open
#147
of 193 outputs
Altmetric has tracked 24,837,702 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,012 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 129.5. This one is in the 26th percentile – i.e., 26% 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 357,795 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 84% of its contemporaries.
We're also able to compare this research output to 193 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.