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Deep learning for real-time auxiliary diagnosis of pancreatic cancer in endoscopic ultrasonography

Overview of attention for article published in Frontiers in oncology, October 2022
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

twitter
4 X users

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
9 Mendeley
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Title
Deep learning for real-time auxiliary diagnosis of pancreatic cancer in endoscopic ultrasonography
Published in
Frontiers in oncology, October 2022
DOI 10.3389/fonc.2022.973652
Pubmed ID
Authors

Guo Tian, Danxia Xu, Yinghua He, Weilu Chai, Zhuang Deng, Chao Cheng, Xinyan Jin, Guyue Wei, Qiyu Zhao, Tianan Jiang

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 2 22%
Researcher 1 11%
Student > Postgraduate 1 11%
Other 1 11%
Unknown 4 44%
Readers by discipline Count As %
Engineering 2 22%
Unknown 7 78%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 26 October 2022.
All research outputs
#16,337,915
of 26,246,850 outputs
Outputs from Frontiers in oncology
#5,222
of 22,949 outputs
Outputs of similar age
#215,490
of 446,006 outputs
Outputs of similar age from Frontiers in oncology
#361
of 1,712 outputs
Altmetric has tracked 26,246,850 research outputs across all sources so far. This one is in the 36th percentile – i.e., 36% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,949 research outputs from this source. They receive a mean Attention Score of 3.2. This one has gotten more attention than average, scoring higher than 74% of its peers.
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 446,006 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,712 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.