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Chronic kidney disease prediction using machine learning techniques

Overview of attention for article published in Journal of Big Data, November 2022
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
1 X user

Citations

dimensions_citation
29 Dimensions

Readers on

mendeley
112 Mendeley
Title
Chronic kidney disease prediction using machine learning techniques
Published in
Journal of Big Data, November 2022
DOI 10.1186/s40537-022-00657-5
Authors

Dibaba Adeba Debal, Tilahun Melak Sitote

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

Geographical breakdown

Country Count As %
Unknown 112 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 6%
Researcher 7 6%
Student > Bachelor 7 6%
Student > Master 6 5%
Professor > Associate Professor 3 3%
Other 6 5%
Unknown 76 68%
Readers by discipline Count As %
Computer Science 23 21%
Engineering 6 5%
Arts and Humanities 2 2%
Mathematics 1 <1%
Business, Management and Accounting 1 <1%
Other 4 4%
Unknown 75 67%
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 17 July 2023.
All research outputs
#16,352,264
of 24,092,222 outputs
Outputs from Journal of Big Data
#219
of 363 outputs
Outputs of similar age
#257,565
of 456,486 outputs
Outputs of similar age from Journal of Big Data
#5
of 10 outputs
Altmetric has tracked 24,092,222 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 363 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.6. This one is in the 25th percentile – i.e., 25% 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 456,486 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.