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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A deep learning method for counting white blood cells in bone marrow images
|
|---|---|
| Published in |
BMC Bioinformatics, November 2021
|
| DOI | 10.1186/s12859-021-04003-z |
| Pubmed ID | |
| Authors |
Da Wang, Maxwell Hwang, Wei-Cheng Jiang, Kefeng Ding, Hsiao Chien Chang, Kao-Shing Hwang |
X Demographics
The data shown below were collected from the profiles of 2 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 | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 44 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 3 | 7% |
| Student > Ph. D. Student | 3 | 7% |
| Researcher | 2 | 5% |
| Professor | 2 | 5% |
| Lecturer | 1 | 2% |
| Other | 4 | 9% |
| Unknown | 29 | 66% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 7 | 16% |
| Computer Science | 4 | 9% |
| Economics, Econometrics and Finance | 1 | 2% |
| Unspecified | 1 | 2% |
| Medicine and Dentistry | 1 | 2% |
| Other | 1 | 2% |
| Unknown | 29 | 66% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 03 November 2022.
All research outputs
#3,777,324
of 23,344,526 outputs
Outputs from BMC Bioinformatics
#1,385
of 7,388 outputs
Outputs of similar age
#82,169
of 439,423 outputs
Outputs of similar age from BMC Bioinformatics
#44
of 169 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,388 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 well, scoring higher than 80% 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 439,423 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 169 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 72% of its contemporaries.