| Title |
Denoising and artefact removal for transthoracic echocardiographic imaging in congenital heart disease: utility of diagnosis specific deep learning algorithms
|
|---|---|
| Published in |
The International Journal of Cardiovascular Imaging, July 2019
|
| DOI | 10.1007/s10554-019-01671-0 |
| Pubmed ID | |
| Authors |
Gerhard-Paul Diller, Astrid E. Lammers, Sonya Babu-Narayan, Wei Li, Robert M. Radke, Helmut Baumgartner, Michael A. Gatzoulis, Stefan Orwat |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| China | 1 | 20% |
| United States | 1 | 20% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Practitioners (doctors, other healthcare professionals) | 1 | 20% |
| Science communicators (journalists, bloggers, editors) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 42 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 12% |
| Student > Master | 5 | 12% |
| Student > Ph. D. Student | 4 | 10% |
| Other | 3 | 7% |
| Student > Bachelor | 2 | 5% |
| Other | 5 | 12% |
| Unknown | 18 | 43% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 8 | 19% |
| Computer Science | 6 | 14% |
| Engineering | 2 | 5% |
| Economics, Econometrics and Finance | 1 | 2% |
| Arts and Humanities | 1 | 2% |
| Other | 2 | 5% |
| Unknown | 22 | 52% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 06 December 2019.
All research outputs
#14,920,631
of 25,385,509 outputs
Outputs from The International Journal of Cardiovascular Imaging
#582
of 2,012 outputs
Outputs of similar age
#181,076
of 358,190 outputs
Outputs of similar age from The International Journal of Cardiovascular Imaging
#14
of 38 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,012 research outputs from this source. They receive a mean Attention Score of 2.3. This one has gotten more attention than average, scoring higher than 69% 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 358,190 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 38 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 63% of its contemporaries.