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Multichannel DenseNet Architecture for Classification of Mammographic Breast Density for Breast Cancer Detection

Overview of attention for article published in Frontiers in Public Health, April 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 (68th percentile)

Mentioned by

twitter
3 X users

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
28 Mendeley
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Title
Multichannel DenseNet Architecture for Classification of Mammographic Breast Density for Breast Cancer Detection
Published in
Frontiers in Public Health, April 2022
DOI 10.3389/fpubh.2022.885212
Pubmed ID
Authors

Shivaji D. Pawar, Kamal K. Sharma, Suhas G. Sapate, Geetanjali Y. Yadav, Roobaea Alroobaea, Sabah M. Alzahrani, Mustapha Hedabou

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 14%
Student > Ph. D. Student 2 7%
Student > Postgraduate 2 7%
Student > Bachelor 1 4%
Unspecified 1 4%
Other 0 0%
Unknown 18 64%
Readers by discipline Count As %
Computer Science 4 14%
Unspecified 1 4%
Nursing and Health Professions 1 4%
Pharmacology, Toxicology and Pharmaceutical Science 1 4%
Economics, Econometrics and Finance 1 4%
Other 1 4%
Unknown 19 68%
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 13 May 2022.
All research outputs
#14,848,792
of 23,755,107 outputs
Outputs from Frontiers in Public Health
#4,014
of 11,456 outputs
Outputs of similar age
#217,596
of 444,886 outputs
Outputs of similar age from Frontiers in Public Health
#300
of 1,089 outputs
Altmetric has tracked 23,755,107 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,456 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.4. This one has gotten more attention than average, scoring higher than 61% 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 444,886 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,089 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 68% of its contemporaries.