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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

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2 X users

Citations

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40 Dimensions

Readers on

mendeley
52 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

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 52 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 12%
Student > Master 6 12%
Student > Ph. D. Student 6 12%
Student > Postgraduate 4 8%
Researcher 4 8%
Other 4 8%
Unknown 22 42%
Readers by discipline Count As %
Medicine and Dentistry 8 15%
Computer Science 8 15%
Engineering 7 13%
Nursing and Health Professions 2 4%
Physics and Astronomy 2 4%
Other 4 8%
Unknown 21 40%
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 30 January 2019.
All research outputs
#18,005,961
of 23,125,690 outputs
Outputs from Journal of Digital Imaging
#821
of 1,070 outputs
Outputs of similar age
#249,393
of 348,908 outputs
Outputs of similar age from Journal of Digital Imaging
#25
of 37 outputs
Altmetric has tracked 23,125,690 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,070 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 18th percentile – i.e., 18% 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 348,908 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.