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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Post-processing radio-frequency signal based on deep learning method for ultrasonic microbubble imaging
|
|---|---|
| Published in |
BioMedical Engineering OnLine, September 2019
|
| DOI | 10.1186/s12938-019-0714-6 |
| Pubmed ID | |
| Authors |
Meng Dai, Shuying Li, Yuanyuan Wang, Qi Zhang, Jinhua Yu |
X Demographics
The data shown below were collected from the profiles of 7 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 | 3 | 43% |
| Nepal | 1 | 14% |
| Peru | 1 | 14% |
| Unknown | 2 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 86% |
| Scientists | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 32 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 16% |
| Student > Bachelor | 3 | 9% |
| Student > Master | 3 | 9% |
| Researcher | 3 | 9% |
| Unspecified | 2 | 6% |
| Other | 3 | 9% |
| Unknown | 13 | 41% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 8 | 25% |
| Medicine and Dentistry | 4 | 13% |
| Biochemistry, Genetics and Molecular Biology | 2 | 6% |
| Unspecified | 2 | 6% |
| Social Sciences | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 15 | 47% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 12 September 2019.
All research outputs
#7,279,833
of 23,163,378 outputs
Outputs from BioMedical Engineering OnLine
#197
of 827 outputs
Outputs of similar age
#127,769
of 341,069 outputs
Outputs of similar age from BioMedical Engineering OnLine
#3
of 7 outputs
Altmetric has tracked 23,163,378 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 827 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 75% 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 341,069 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.