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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep Learning for Cardiac Image Segmentation: A Review
|
|---|---|
| Published in |
Frontiers in Cardiovascular Medicine, March 2020
|
| DOI | 10.3389/fcvm.2020.00025 |
| Pubmed ID | |
| Authors |
Chen Chen, Chen Qin, Huaqi Qiu, Giacomo Tarroni, Jinming Duan, Wenjia Bai, Daniel Rueckert |
X Demographics
The data shown below were collected from the profiles of 26 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 Kingdom | 5 | 19% |
| United States | 2 | 8% |
| Switzerland | 2 | 8% |
| Spain | 1 | 4% |
| Canada | 1 | 4% |
| India | 1 | 4% |
| New Zealand | 1 | 4% |
| Italy | 1 | 4% |
| Nepal | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 9 | 35% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 16 | 62% |
| Scientists | 7 | 27% |
| Practitioners (doctors, other healthcare professionals) | 2 | 8% |
| Science communicators (journalists, bloggers, editors) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 926 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 926 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 146 | 16% |
| Student > Master | 104 | 11% |
| Researcher | 85 | 9% |
| Student > Bachelor | 74 | 8% |
| Student > Doctoral Student | 35 | 4% |
| Other | 108 | 12% |
| Unknown | 374 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 188 | 20% |
| Engineering | 162 | 17% |
| Medicine and Dentistry | 56 | 6% |
| Physics and Astronomy | 24 | 3% |
| Biochemistry, Genetics and Molecular Biology | 14 | 2% |
| Other | 73 | 8% |
| Unknown | 409 | 44% |
Attention Score in Context
This research output has an Altmetric Attention Score of 18. 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 27 April 2023.
All research outputs
#2,040,585
of 25,387,668 outputs
Outputs from Frontiers in Cardiovascular Medicine
#243
of 9,241 outputs
Outputs of similar age
#48,190
of 386,389 outputs
Outputs of similar age from Frontiers in Cardiovascular Medicine
#11
of 58 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,241 research outputs from this source. They receive a mean Attention Score of 4.4. 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 386,389 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 87% of its contemporaries.
We're also able to compare this research output to 58 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.