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Resource-efficient fast prediction in healthcare data analytics: A pruned Random Forest regression approach

Overview of attention for article published in Computing, January 2020
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1 X user

Citations

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16 Dimensions

Readers on

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38 Mendeley
Title
Resource-efficient fast prediction in healthcare data analytics: A pruned Random Forest regression approach
Published in
Computing, January 2020
DOI 10.1007/s00607-019-00785-6
Authors

Khaled Fawagreh, Mohamed Medhat Gaber

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 8%
Lecturer 2 5%
Student > Bachelor 2 5%
Lecturer > Senior Lecturer 2 5%
Student > Postgraduate 2 5%
Other 4 11%
Unknown 23 61%
Readers by discipline Count As %
Computer Science 6 16%
Engineering 3 8%
Business, Management and Accounting 2 5%
Psychology 1 3%
Biochemistry, Genetics and Molecular Biology 1 3%
Other 0 0%
Unknown 25 66%
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 28 April 2020.
All research outputs
#19,854,405
of 24,395,432 outputs
Outputs from Computing
#202
of 236 outputs
Outputs of similar age
#344,615
of 464,937 outputs
Outputs of similar age from Computing
#4
of 5 outputs
Altmetric has tracked 24,395,432 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 236 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 8th percentile – i.e., 8% 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 464,937 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one.