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.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
Title |
Deep learning-based image segmentation model using an MRI-based convolutional neural network for physiological evaluation of the heart
|
---|---|
Published in |
Frontiers in Physiology, March 2023
|
DOI | 10.3389/fphys.2023.1148717 |
Pubmed ID | |
Authors |
Wanni Xu, Jianshe Shi, Yunling Lin, Chao Liu, Weifang Xie, Huifang Liu, Siyu Huang, Daxin Zhu, Lianta Su, Yifeng Huang, Yuguang Ye, Jianlong Huang |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Switzerland | 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 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 8 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Unspecified | 1 | 13% |
Student > Ph. D. Student | 1 | 13% |
Student > Master | 1 | 13% |
Unknown | 5 | 63% |
Readers by discipline | Count | As % |
---|---|---|
Unspecified | 1 | 13% |
Physics and Astronomy | 1 | 13% |
Unknown | 6 | 75% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 09 April 2023.
All research outputs
#15,313,961
of 23,549,388 outputs
Outputs from Frontiers in Physiology
#5,946
of 14,265 outputs
Outputs of similar age
#153,401
of 305,901 outputs
Outputs of similar age from Frontiers in Physiology
#129
of 476 outputs
Altmetric has tracked 23,549,388 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,265 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one has gotten more attention than average, scoring higher than 51% 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 305,901 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 476 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 65% of its contemporaries.