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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Integration of longitudinal deep-radiomics and clinical data improves the prediction of durable benefits to anti-PD-1/PD-L1 immunotherapy in advanced NSCLC patients
|
|---|---|
| Published in |
Journal of Translational Medicine, March 2023
|
| DOI | 10.1186/s12967-023-04004-x |
| Pubmed ID | |
| Authors |
Benito Farina, Ana Delia Ramos Guerra, David Bermejo-Peláez, Carmelo Palacios Miras, Andrés Alcazar Peral, Guillermo Gallardo Madueño, Jesús Corral Jaime, Anna Vilalta-Lacarra, Jaime Rubio Pérez, Arrate Muñoz-Barrutia, German R. Peces-Barba, Luis Seijo Maceiras, Ignacio Gil-Bazo, Manuel Dómine Gómez, María J. Ledesma-Carbayo |
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 % |
|---|---|---|
| Italy | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 20 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 3 | 15% |
| Student > Postgraduate | 2 | 10% |
| Student > Ph. D. Student | 2 | 10% |
| Researcher | 2 | 10% |
| Student > Doctoral Student | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 9 | 45% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 2 | 10% |
| Sports and Recreations | 2 | 10% |
| Mathematics | 1 | 5% |
| Business, Management and Accounting | 1 | 5% |
| Biochemistry, Genetics and Molecular Biology | 1 | 5% |
| Other | 3 | 15% |
| Unknown | 10 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 66. 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 May 2023.
All research outputs
#604,701
of 24,254,113 outputs
Outputs from Journal of Translational Medicine
#124
of 4,322 outputs
Outputs of similar age
#13,288
of 408,524 outputs
Outputs of similar age from Journal of Translational Medicine
#5
of 145 outputs
Altmetric has tracked 24,254,113 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,322 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one has done particularly well, scoring higher than 97% 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 408,524 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 145 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.