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Automatic Lumbar MRI Detection and Identification Based on Deep Learning

Overview of attention for article published in Journal of Digital Imaging, October 2018
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Mentioned by

twitter
2 tweeters

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
12 Mendeley
Title
Automatic Lumbar MRI Detection and Identification Based on Deep Learning
Published in
Journal of Digital Imaging, October 2018
DOI 10.1007/s10278-018-0130-7
Pubmed ID
Authors

Yujing Zhou, Yuan Liu, Qian Chen, Guohua Gu, Xiubao Sui

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 58%
Student > Postgraduate 1 8%
Student > Bachelor 1 8%
Student > Ph. D. Student 1 8%
Student > Doctoral Student 1 8%
Other 1 8%
Readers by discipline Count As %
Medicine and Dentistry 7 58%
Physics and Astronomy 2 17%
Computer Science 1 8%
Psychology 1 8%
Engineering 1 8%
Other 0 0%

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 30 January 2019.
All research outputs
#10,152,119
of 13,297,120 outputs
Outputs from Journal of Digital Imaging
#503
of 657 outputs
Outputs of similar age
#193,412
of 283,165 outputs
Outputs of similar age from Journal of Digital Imaging
#9
of 15 outputs
Altmetric has tracked 13,297,120 research outputs across all sources so far. This one is in the 20th percentile – i.e., 20% of other outputs scored the same or lower than it.
So far Altmetric has tracked 657 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 16th percentile – i.e., 16% 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 283,165 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.