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Explainable machine learning for breast cancer diagnosis from mammography and ultrasound images: a systematic review

Overview of attention for article published in BMJ Health & Care Informatics, February 2024
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1 X user

Readers on

mendeley
44 Mendeley
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Title
Explainable machine learning for breast cancer diagnosis from mammography and ultrasound images: a systematic review
Published in
BMJ Health & Care Informatics, February 2024
DOI 10.1136/bmjhci-2023-100954
Pubmed ID
Authors

Daraje kaba Gurmessa, Worku Jimma

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

Geographical breakdown

Country Count As %
Unknown 44 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 14%
Researcher 5 11%
Unspecified 3 7%
Professor > Associate Professor 2 5%
Student > Bachelor 2 5%
Other 4 9%
Unknown 22 50%
Readers by discipline Count As %
Computer Science 6 14%
Engineering 4 9%
Medicine and Dentistry 4 9%
Biochemistry, Genetics and Molecular Biology 3 7%
Unspecified 3 7%
Other 1 2%
Unknown 23 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 21 February 2024.
All research outputs
#21,506,435
of 26,399,279 outputs
Outputs from BMJ Health & Care Informatics
#450
of 512 outputs
Outputs of similar age
#267,466
of 380,144 outputs
Outputs of similar age from BMJ Health & Care Informatics
#11
of 11 outputs
Altmetric has tracked 26,399,279 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 512 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.0. This one is in the 3rd percentile – i.e., 3% 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 380,144 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 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.