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Deep-learning based quantification model for hip bone marrow edema and synovitis in patients with spondyloarthritis based on magnetic resonance images

Overview of attention for article published in Frontiers in Physiology, March 2023
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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2 X users

Citations

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5 Dimensions

Readers on

mendeley
7 Mendeley
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Title
Deep-learning based quantification model for hip bone marrow edema and synovitis in patients with spondyloarthritis based on magnetic resonance images
Published in
Frontiers in Physiology, March 2023
DOI 10.3389/fphys.2023.1132214
Pubmed ID
Authors

Yan Zheng, Chao Bai, Kui Zhang, Qing Han, Qingbiao Guan, Ying Liu, Zhaohui Zheng, Yong Xia, Ping Zhu

X Demographics

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 29%
Lecturer 1 14%
Student > Ph. D. Student 1 14%
Unknown 3 43%
Readers by discipline Count As %
Engineering 3 43%
Computer Science 1 14%
Unknown 3 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 20 March 2023.
All research outputs
#19,012,063
of 23,572,442 outputs
Outputs from Frontiers in Physiology
#8,539
of 14,279 outputs
Outputs of similar age
#274,626
of 400,678 outputs
Outputs of similar age from Frontiers in Physiology
#260
of 586 outputs
Altmetric has tracked 23,572,442 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,279 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
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 400,678 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 586 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.