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Enhancing Performance of Breast Ultrasound in Opportunistic Screening Women by a Deep Learning-Based System: A Multicenter Prospective Study

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

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

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2 X users

Citations

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14 Dimensions

Readers on

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11 Mendeley
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Title
Enhancing Performance of Breast Ultrasound in Opportunistic Screening Women by a Deep Learning-Based System: A Multicenter Prospective Study
Published in
Frontiers in oncology, February 2022
DOI 10.3389/fonc.2022.804632
Pubmed ID
Authors

Chenyang Zhao, Mengsu Xiao, Li Ma, Xinhua Ye, Jing Deng, Ligang Cui, Fajin Guo, Min Wu, Baoming Luo, Qin Chen, Wu Chen, Jun Guo, Qian Li, Qing Zhang, Jianchu Li, Yuxin Jiang, Qingli Zhu

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

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 18%
Researcher 1 9%
Student > Postgraduate 1 9%
Unknown 7 64%
Readers by discipline Count As %
Medicine and Dentistry 2 18%
Computer Science 2 18%
Arts and Humanities 1 9%
Unknown 6 55%
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 01 March 2022.
All research outputs
#17,285,374
of 26,166,431 outputs
Outputs from Frontiers in oncology
#6,849
of 22,913 outputs
Outputs of similar age
#304,195
of 537,696 outputs
Outputs of similar age from Frontiers in oncology
#424
of 1,458 outputs
Altmetric has tracked 26,166,431 research outputs across all sources so far. This one is in the 31st percentile – i.e., 31% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,913 research outputs from this source. They receive a mean Attention Score of 3.1. This one has gotten more attention than average, scoring higher than 64% 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 537,696 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,458 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.