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Channel-Unet: A Spatial Channel-Wise Convolutional Neural Network for Liver and Tumors Segmentation

Overview of attention for article published in Frontiers in Genetics, November 2019
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Mentioned by

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1 X user

Citations

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96 Dimensions

Readers on

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69 Mendeley
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Title
Channel-Unet: A Spatial Channel-Wise Convolutional Neural Network for Liver and Tumors Segmentation
Published in
Frontiers in Genetics, November 2019
DOI 10.3389/fgene.2019.01110
Pubmed ID
Authors

Yilong Chen, Kai Wang, Xiangyun Liao, Yinling Qian, Qiong Wang, Zhiyong Yuan, Pheng-Ann Heng

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 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 69 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 20%
Student > Master 11 16%
Researcher 5 7%
Student > Bachelor 4 6%
Lecturer > Senior Lecturer 3 4%
Other 7 10%
Unknown 25 36%
Readers by discipline Count As %
Computer Science 16 23%
Engineering 10 14%
Medicine and Dentistry 5 7%
Agricultural and Biological Sciences 2 3%
Social Sciences 2 3%
Other 5 7%
Unknown 29 42%
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 21 December 2019.
All research outputs
#20,595,624
of 23,182,015 outputs
Outputs from Frontiers in Genetics
#8,810
of 12,215 outputs
Outputs of similar age
#384,413
of 459,063 outputs
Outputs of similar age from Frontiers in Genetics
#270
of 342 outputs
Altmetric has tracked 23,182,015 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 12,215 research outputs from this source. They receive a mean Attention Score of 3.7. 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 459,063 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 342 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.