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Mendeley readers
Attention Score in Context
| Title |
Large-scale computations on histology images reveal grade-differentiating parameters for breast cancer
|
|---|---|
| Published in |
BMC Medical Imaging, October 2006
|
| DOI | 10.1186/1471-2342-6-14 |
| Pubmed ID | |
| Authors |
Sokol Petushi, Fernando U Garcia, Marian M Haber, Constantine Katsinis, Aydin Tozeren |
| Abstract |
Tumor classification is inexact and largely dependent on the qualitative pathological examination of the images of the tumor tissue slides. In this study, our aim was to develop an automated computational method to classify Hematoxylin and Eosin (H&E) stained tissue sections based on cancer tissue texture features. |
Mendeley readers
The data shown below were compiled from readership statistics for 183 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 4 | 2% |
| Netherlands | 2 | 1% |
| Japan | 2 | 1% |
| Switzerland | 1 | <1% |
| Germany | 1 | <1% |
| Canada | 1 | <1% |
| Colombia | 1 | <1% |
| Belgium | 1 | <1% |
| United States | 1 | <1% |
| Other | 0 | 0% |
| Unknown | 169 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 46 | 25% |
| Student > Master | 29 | 16% |
| Student > Bachelor | 22 | 12% |
| Researcher | 20 | 11% |
| Other | 9 | 5% |
| Other | 25 | 14% |
| Unknown | 32 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 56 | 31% |
| Engineering | 39 | 21% |
| Medicine and Dentistry | 21 | 11% |
| Agricultural and Biological Sciences | 9 | 5% |
| Physics and Astronomy | 7 | 4% |
| Other | 14 | 8% |
| Unknown | 37 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 October 2019.
All research outputs
#3,102,400
of 22,694,633 outputs
Outputs from BMC Medical Imaging
#20
of 588 outputs
Outputs of similar age
#7,155
of 68,367 outputs
Outputs of similar age from BMC Medical Imaging
#1
of 1 outputs
Altmetric has tracked 22,694,633 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 588 research outputs from this source. They receive a mean Attention Score of 2.1. This one has done particularly well, scoring higher than 95% 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 68,367 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 89% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them