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X Demographics
Mendeley readers
Attention Score in Context
| Title |
An 8-gene machine learning model improves clinical prediction of severe dengue progression
|
|---|---|
| Published in |
Genome Medicine, March 2022
|
| DOI | 10.1186/s13073-022-01034-w |
| Pubmed ID | |
| Authors |
Yiran E. Liu, Sirle Saul, Aditya Manohar Rao, Makeda Lucretia Robinson, Olga Lucia Agudelo Rojas, Ana Maria Sanz, Michelle Verghese, Daniel Solis, Mamdouh Sibai, Chun Hong Huang, Malaya Kumar Sahoo, Rosa Margarita Gelvez, Nathalia Bueno, Maria Isabel Estupiñan Cardenas, Luis Angel Villar Centeno, Elsa Marina Rojas Garrido, Fernando Rosso, Michele Donato, Benjamin A. Pinsky, Shirit Einav, Purvesh Khatri |
X Demographics
The data shown below were collected from the profiles of 14 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 | 4 | 29% |
| United Kingdom | 2 | 14% |
| India | 1 | 7% |
| Hong Kong | 1 | 7% |
| Unknown | 6 | 43% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 6 | 43% |
| Members of the public | 6 | 43% |
| Science communicators (journalists, bloggers, editors) | 1 | 7% |
| Practitioners (doctors, other healthcare professionals) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 55 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 7 | 13% |
| Researcher | 6 | 11% |
| Student > Master | 4 | 7% |
| Student > Doctoral Student | 3 | 5% |
| Lecturer | 3 | 5% |
| Other | 7 | 13% |
| Unknown | 25 | 45% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 10 | 18% |
| Agricultural and Biological Sciences | 3 | 5% |
| Social Sciences | 3 | 5% |
| Computer Science | 2 | 4% |
| Immunology and Microbiology | 2 | 4% |
| Other | 10 | 18% |
| Unknown | 25 | 45% |
Attention Score in Context
This research output has an Altmetric Attention Score of 51. 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 26 May 2022.
All research outputs
#778,174
of 24,302,917 outputs
Outputs from Genome Medicine
#148
of 1,500 outputs
Outputs of similar age
#19,850
of 432,108 outputs
Outputs of similar age from Genome Medicine
#8
of 32 outputs
Altmetric has tracked 24,302,917 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,500 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.6. This one has done particularly well, scoring higher than 90% 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 432,108 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 95% of its contemporaries.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.