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Sample size determination for biomedical big data with limited labels

Overview of attention for article published in Network Modeling Analysis in Health Informatics and Bioinformatics, January 2020
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Mentioned by

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2 X users

Citations

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12 Dimensions

Readers on

mendeley
34 Mendeley
Title
Sample size determination for biomedical big data with limited labels
Published in
Network Modeling Analysis in Health Informatics and Bioinformatics, January 2020
DOI 10.1007/s13721-020-0218-0
Authors

Aaron N. Richter, Taghi M. Khoshgoftaar

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

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 6 18%
Researcher 3 9%
Lecturer 3 9%
Student > Ph. D. Student 3 9%
Other 2 6%
Other 6 18%
Unknown 11 32%
Readers by discipline Count As %
Engineering 7 21%
Business, Management and Accounting 5 15%
Computer Science 3 9%
Medicine and Dentistry 2 6%
Energy 1 3%
Other 3 9%
Unknown 13 38%
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 13 January 2020.
All research outputs
#19,516,978
of 23,999,200 outputs
Outputs from Network Modeling Analysis in Health Informatics and Bioinformatics
#31
of 43 outputs
Outputs of similar age
#341,523
of 462,148 outputs
Outputs of similar age from Network Modeling Analysis in Health Informatics and Bioinformatics
#2
of 2 outputs
Altmetric has tracked 23,999,200 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 43 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.4. This one scored the same or higher as 12 of them.
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 462,148 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 2 others from the same source and published within six weeks on either side of this one.