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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A fully automated micro‑CT deep learning approach for precision preclinical investigation of lung fibrosis progression and response to therapy
|
|---|---|
| Published in |
Respiratory Research, May 2023
|
| DOI | 10.1186/s12931-023-02432-3 |
| Pubmed ID | |
| Authors |
Martina Buccardi, Erica Ferrini, Francesca Pennati, Elena Vincenzi, Roberta Eufrasia Ledda, Andrea Grandi, Davide Buseghin, Gino Villetti, Nicola Sverzellati, Andrea Aliverti, Franco Fabio Stellari |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 33% |
| Netherlands | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 33% |
| Members of the public | 1 | 33% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 14 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 36% |
| Student > Ph. D. Student | 2 | 14% |
| Unspecified | 1 | 7% |
| Professor | 1 | 7% |
| Unknown | 5 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 2 | 14% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 14% |
| Veterinary Science and Veterinary Medicine | 1 | 7% |
| Unspecified | 1 | 7% |
| Medicine and Dentistry | 1 | 7% |
| Other | 1 | 7% |
| Unknown | 6 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 15. 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 23 May 2023.
All research outputs
#2,407,543
of 25,394,764 outputs
Outputs from Respiratory Research
#244
of 3,064 outputs
Outputs of similar age
#46,204
of 400,871 outputs
Outputs of similar age from Respiratory Research
#7
of 66 outputs
Altmetric has tracked 25,394,764 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 91% 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 400,871 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 88% of its contemporaries.
We're also able to compare this research output to 66 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.