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Ada-WHIPS: explaining AdaBoost classification with applications in the health sciences

Overview of attention for article published in BMC Medical Informatics and Decision Making, October 2020
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Mentioned by

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2 X users

Citations

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46 Dimensions

Readers on

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108 Mendeley
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Title
Ada-WHIPS: explaining AdaBoost classification with applications in the health sciences
Published in
BMC Medical Informatics and Decision Making, October 2020
DOI 10.1186/s12911-020-01201-2
Pubmed ID
Authors

Julian Hatwell, Mohamed Medhat Gaber, R. Muhammad Atif Azad

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 108 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 108 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 12 11%
Student > Master 11 10%
Student > Ph. D. Student 9 8%
Student > Doctoral Student 6 6%
Researcher 6 6%
Other 11 10%
Unknown 53 49%
Readers by discipline Count As %
Computer Science 23 21%
Engineering 11 10%
Medicine and Dentistry 6 6%
Biochemistry, Genetics and Molecular Biology 5 5%
Business, Management and Accounting 4 4%
Other 7 6%
Unknown 52 48%
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 11 October 2020.
All research outputs
#18,090,068
of 23,245,494 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,525
of 2,022 outputs
Outputs of similar age
#293,367
of 412,242 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#38
of 50 outputs
Altmetric has tracked 23,245,494 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 2,022 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 21st percentile – i.e., 21% 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 412,242 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 50 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.