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X Demographics
Mendeley readers
Attention Score in Context
Title |
Machine learning with the TCGA-HNSC dataset: improving usability by addressing inconsistency, sparsity, and high-dimensionality
|
---|---|
Published in |
BMC Bioinformatics, June 2019
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DOI | 10.1186/s12859-019-2929-8 |
Pubmed ID | |
Authors |
Michael C. Rendleman, John M. Buatti, Terry A. Braun, Brian J. Smith, Chibuzo Nwakama, Reinhard R. Beichel, Bart Brown, Thomas L. Casavant |
X Demographics
The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Australia | 2 | 20% |
United States | 2 | 20% |
Spain | 1 | 10% |
United Kingdom | 1 | 10% |
Unknown | 4 | 40% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 6 | 60% |
Members of the public | 3 | 30% |
Practitioners (doctors, other healthcare professionals) | 1 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 78 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 14 | 18% |
Student > Bachelor | 13 | 17% |
Student > Ph. D. Student | 9 | 12% |
Student > Master | 9 | 12% |
Other | 4 | 5% |
Other | 8 | 10% |
Unknown | 21 | 27% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 11 | 14% |
Biochemistry, Genetics and Molecular Biology | 10 | 13% |
Medicine and Dentistry | 10 | 13% |
Agricultural and Biological Sciences | 9 | 12% |
Engineering | 2 | 3% |
Other | 13 | 17% |
Unknown | 23 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 29 June 2019.
All research outputs
#2,814,660
of 23,885,338 outputs
Outputs from BMC Bioinformatics
#875
of 7,484 outputs
Outputs of similar age
#58,830
of 354,409 outputs
Outputs of similar age from BMC Bioinformatics
#28
of 169 outputs
Altmetric has tracked 23,885,338 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,484 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 88% of its peers.
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 354,409 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 169 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.