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X Demographics
Mendeley readers
Attention Score in Context
Title |
A fully automated deep learning pipeline for micro-CT-imaging-based densitometry of lung fibrosis murine models
|
---|---|
Published in |
Respiratory Research, November 2022
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DOI | 10.1186/s12931-022-02236-x |
Pubmed ID | |
Authors |
Elena Vincenzi, Alice Fantazzini, Curzio Basso, Annalisa Barla, Francesca Odone, Ludovica Leo, Laura Mecozzi, Martina Mambrini, Erica Ferrini, Nicola Sverzellati, Franco Fabio Stellari |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Netherlands | 1 | 17% |
Italy | 1 | 17% |
South Africa | 1 | 17% |
India | 1 | 17% |
United States | 1 | 17% |
Unknown | 1 | 17% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 5 | 83% |
Practitioners (doctors, other healthcare professionals) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 26 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 7 | 27% |
Student > Ph. D. Student | 4 | 15% |
Unspecified | 1 | 4% |
Other | 1 | 4% |
Lecturer | 1 | 4% |
Other | 2 | 8% |
Unknown | 10 | 38% |
Readers by discipline | Count | As % |
---|---|---|
Engineering | 4 | 15% |
Biochemistry, Genetics and Molecular Biology | 2 | 8% |
Computer Science | 2 | 8% |
Nursing and Health Professions | 1 | 4% |
Physics and Astronomy | 1 | 4% |
Other | 3 | 12% |
Unknown | 13 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. 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 16 May 2023.
All research outputs
#2,287,928
of 25,392,582 outputs
Outputs from Respiratory Research
#228
of 3,064 outputs
Outputs of similar age
#46,860
of 437,028 outputs
Outputs of similar age from Respiratory Research
#2
of 79 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,064 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.9. This one has done particularly well, scoring higher than 92% 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 437,028 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 89% of its contemporaries.
We're also able to compare this research output to 79 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.