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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Improving the Generalizability of Convolutional Neural Network-Based Segmentation on CMR Images
|
|---|---|
| Published in |
Frontiers in Cardiovascular Medicine, June 2020
|
| DOI | 10.3389/fcvm.2020.00105 |
| Pubmed ID | |
| Authors |
Chen Chen, Wenjia Bai, Rhodri H. Davies, Anish N. Bhuva, Charlotte H. Manisty, Joao B. Augusto, James C Moon, Nay Aung, Aaron M. Lee, Mihir M. Sanghvi, Kenneth Fung, Jose Miguel Paiva, Steffen E. Petersen, Elena Lukaschuk, Stefan K. Piechnik, Stefan Neubauer, Daniel Rueckert |
X Demographics
The data shown below were collected from the profiles of 18 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 | 28% |
| Germany | 2 | 11% |
| Switzerland | 1 | 6% |
| United States | 1 | 6% |
| New Zealand | 1 | 6% |
| Netherlands | 1 | 6% |
| Unknown | 7 | 39% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 44% |
| Scientists | 7 | 39% |
| Practitioners (doctors, other healthcare professionals) | 3 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 128 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 128 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 20 | 16% |
| Student > Master | 14 | 11% |
| Researcher | 14 | 11% |
| Student > Bachelor | 13 | 10% |
| Student > Doctoral Student | 8 | 6% |
| Other | 15 | 12% |
| Unknown | 44 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 21 | 16% |
| Medicine and Dentistry | 20 | 16% |
| Engineering | 17 | 13% |
| Unspecified | 4 | 3% |
| Neuroscience | 4 | 3% |
| Other | 11 | 9% |
| Unknown | 51 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 02 September 2020.
All research outputs
#3,685,366
of 25,385,509 outputs
Outputs from Frontiers in Cardiovascular Medicine
#561
of 9,241 outputs
Outputs of similar age
#95,584
of 432,344 outputs
Outputs of similar age from Frontiers in Cardiovascular Medicine
#8
of 58 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% 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 93% 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 432,344 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 77% 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 86% of its contemporaries.