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Machine learning associated with respiratory oscillometry: a computer-aided diagnosis system for the detection of respiratory abnormalities in systemic sclerosis

Overview of attention for article published in BioMedical Engineering OnLine, March 2021
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 X users

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
28 Mendeley
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Title
Machine learning associated with respiratory oscillometry: a computer-aided diagnosis system for the detection of respiratory abnormalities in systemic sclerosis
Published in
BioMedical Engineering OnLine, March 2021
DOI 10.1186/s12938-021-00865-9
Pubmed ID
Authors

Domingos S. M. Andrade, Luigi Maciel Ribeiro, Agnaldo J. Lopes, Jorge L. M. Amaral, Pedro L. Melo

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

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 21%
Student > Ph. D. Student 3 11%
Student > Doctoral Student 1 4%
Student > Bachelor 1 4%
Professor 1 4%
Other 5 18%
Unknown 11 39%
Readers by discipline Count As %
Medicine and Dentistry 6 21%
Engineering 3 11%
Biochemistry, Genetics and Molecular Biology 2 7%
Nursing and Health Professions 2 7%
Computer Science 1 4%
Other 2 7%
Unknown 12 43%
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 29 March 2022.
All research outputs
#18,946,996
of 24,149,630 outputs
Outputs from BioMedical Engineering OnLine
#557
of 849 outputs
Outputs of similar age
#307,661
of 428,346 outputs
Outputs of similar age from BioMedical Engineering OnLine
#10
of 14 outputs
Altmetric has tracked 24,149,630 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 849 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 30th percentile – i.e., 30% 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 428,346 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 14 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.