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Deep Learning-Based Pathology Image Analysis Enhances Magee Feature Correlation With Oncotype DX Breast Recurrence Score

Overview of attention for article published in Frontiers in Medicine, June 2022
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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2 X users

Citations

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10 Dimensions

Readers on

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17 Mendeley
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Title
Deep Learning-Based Pathology Image Analysis Enhances Magee Feature Correlation With Oncotype DX Breast Recurrence Score
Published in
Frontiers in Medicine, June 2022
DOI 10.3389/fmed.2022.886763
Pubmed ID
Authors

Hongxiao Li, Jigang Wang, Zaibo Li, Melad Dababneh, Fusheng Wang, Peng Zhao, Geoffrey H. Smith, George Teodoro, Meijie Li, Jun Kong, Xiaoxian Li

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

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 12%
Student > Doctoral Student 1 6%
Student > Bachelor 1 6%
Professor 1 6%
Student > Ph. D. Student 1 6%
Other 1 6%
Unknown 10 59%
Readers by discipline Count As %
Unspecified 2 12%
Computer Science 2 12%
Engineering 2 12%
Medicine and Dentistry 1 6%
Unknown 10 59%
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 02 July 2022.
All research outputs
#18,829,335
of 23,996,152 outputs
Outputs from Frontiers in Medicine
#4,140
of 6,366 outputs
Outputs of similar age
#299,276
of 428,918 outputs
Outputs of similar age from Frontiers in Medicine
#367
of 571 outputs
Altmetric has tracked 23,996,152 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,366 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.9. This one is in the 29th percentile – i.e., 29% 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 428,918 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 571 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.