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Deep Learning vs. Radiomics for Predicting Axillary Lymph Node Metastasis of Breast Cancer Using Ultrasound Images: Don't Forget the Peritumoral Region

Overview of attention for article published in Frontiers in oncology, January 2020
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1 X user

Citations

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181 Dimensions

Readers on

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132 Mendeley
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Title
Deep Learning vs. Radiomics for Predicting Axillary Lymph Node Metastasis of Breast Cancer Using Ultrasound Images: Don't Forget the Peritumoral Region
Published in
Frontiers in oncology, January 2020
DOI 10.3389/fonc.2020.00053
Pubmed ID
Authors

Qiuchang Sun, Xiaona Lin, Yuanshen Zhao, Ling Li, Kai Yan, Dong Liang, Desheng Sun, Zhi-Cheng Li

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

Geographical breakdown

Country Count As %
Unknown 132 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 15%
Student > Master 18 14%
Researcher 12 9%
Other 7 5%
Student > Bachelor 6 5%
Other 14 11%
Unknown 55 42%
Readers by discipline Count As %
Computer Science 23 17%
Medicine and Dentistry 17 13%
Biochemistry, Genetics and Molecular Biology 6 5%
Engineering 5 4%
Neuroscience 3 2%
Other 9 7%
Unknown 69 52%
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 05 March 2020.
All research outputs
#23,154,082
of 25,806,763 outputs
Outputs from Frontiers in oncology
#16,265
of 22,805 outputs
Outputs of similar age
#407,587
of 477,540 outputs
Outputs of similar age from Frontiers in oncology
#300
of 438 outputs
Altmetric has tracked 25,806,763 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 22,805 research outputs from this source. They receive a mean Attention Score of 3.1. 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 477,540 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 438 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.