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Deep learning-based detection system for multiclass lesions on chest radiographs: comparison with observer readings

Overview of attention for article published in European Radiology, November 2019
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Mentioned by

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1 X user

Citations

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62 Dimensions

Readers on

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63 Mendeley
Title
Deep learning-based detection system for multiclass lesions on chest radiographs: comparison with observer readings
Published in
European Radiology, November 2019
DOI 10.1007/s00330-019-06532-x
Pubmed ID
Authors

Sohee Park, Sang Min Lee, Kyung Hee Lee, Kyu-Hwan Jung, Woong Bae, Jooae Choe, Joon Beom Seo

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 63 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 16%
Researcher 8 13%
Student > Ph. D. Student 8 13%
Other 7 11%
Lecturer > Senior Lecturer 3 5%
Other 6 10%
Unknown 21 33%
Readers by discipline Count As %
Medicine and Dentistry 14 22%
Computer Science 12 19%
Engineering 5 8%
Chemistry 2 3%
Social Sciences 2 3%
Other 6 10%
Unknown 22 35%
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 22 November 2019.
All research outputs
#20,590,073
of 23,177,498 outputs
Outputs from European Radiology
#3,370
of 4,192 outputs
Outputs of similar age
#383,224
of 457,697 outputs
Outputs of similar age from European Radiology
#62
of 76 outputs
Altmetric has tracked 23,177,498 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,192 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 1st percentile – i.e., 1% 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 457,697 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 76 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.