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Classifying microscopic images as acute lymphoblastic leukemia by Resnet ensemble model and Taguchi method

Overview of attention for article published in BMC Bioinformatics, January 2022
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Mentioned by

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3 X users

Citations

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10 Dimensions

Readers on

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37 Mendeley
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Title
Classifying microscopic images as acute lymphoblastic leukemia by Resnet ensemble model and Taguchi method
Published in
BMC Bioinformatics, January 2022
DOI 10.1186/s12859-022-04558-5
Pubmed ID
Authors

Yao-Mei Chen, Fu-I Chou, Wen-Hsien Ho, Jinn-Tsong Tsai

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 14 38%
Lecturer 2 5%
Student > Ph. D. Student 2 5%
Student > Master 2 5%
Professor 1 3%
Other 1 3%
Unknown 15 41%
Readers by discipline Count As %
Unspecified 14 38%
Computer Science 2 5%
Engineering 2 5%
Medicine and Dentistry 2 5%
Biochemistry, Genetics and Molecular Biology 1 3%
Other 0 0%
Unknown 16 43%
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 12 January 2022.
All research outputs
#17,800,994
of 22,867,327 outputs
Outputs from BMC Bioinformatics
#5,948
of 7,295 outputs
Outputs of similar age
#341,893
of 503,238 outputs
Outputs of similar age from BMC Bioinformatics
#126
of 138 outputs
Altmetric has tracked 22,867,327 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,295 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 13th percentile – i.e., 13% 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 503,238 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 138 others from the same source and published within six weeks on either side of this one. This one is in the 2nd percentile – i.e., 2% of its contemporaries scored the same or lower than it.