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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Keras R-CNN: library for cell detection in biological images using deep neural networks
|
|---|---|
| Published in |
BMC Bioinformatics, July 2020
|
| DOI | 10.1186/s12859-020-03635-x |
| Pubmed ID | |
| Authors |
Jane Hung, Allen Goodman, Deepali Ravel, Stefanie C. P. Lopes, Gabriel W. Rangel, Odailton A. Nery, Benoit Malleret, Francois Nosten, Marcus V. G. Lacerda, Marcelo U. Ferreira, Laurent Rénia, Manoj T. Duraisingh, Fabio T. M. Costa, Matthias Marti, Anne E. Carpenter |
X Demographics
The data shown below were collected from the profiles of 49 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 | 11 | 22% |
| India | 5 | 10% |
| United Kingdom | 3 | 6% |
| Portugal | 2 | 4% |
| Canada | 1 | 2% |
| France | 1 | 2% |
| Finland | 1 | 2% |
| Netherlands | 1 | 2% |
| Nigeria | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 23 | 47% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 31 | 63% |
| Scientists | 17 | 35% |
| Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 161 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 161 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 20 | 12% |
| Researcher | 20 | 12% |
| Student > Master | 11 | 7% |
| Student > Bachelor | 11 | 7% |
| Student > Doctoral Student | 8 | 5% |
| Other | 24 | 15% |
| Unknown | 67 | 42% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 23 | 14% |
| Biochemistry, Genetics and Molecular Biology | 19 | 12% |
| Engineering | 13 | 8% |
| Agricultural and Biological Sciences | 11 | 7% |
| Medicine and Dentistry | 5 | 3% |
| Other | 17 | 11% |
| Unknown | 73 | 45% |
Attention Score in Context
This research output has an Altmetric Attention Score of 26. 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 08 December 2020.
All research outputs
#1,466,318
of 25,490,562 outputs
Outputs from BMC Bioinformatics
#191
of 7,708 outputs
Outputs of similar age
#41,332
of 430,891 outputs
Outputs of similar age from BMC Bioinformatics
#4
of 121 outputs
Altmetric has tracked 25,490,562 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,708 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 97% 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 430,891 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 121 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.