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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Learning meaningful latent space representations for patient risk stratification: Model development and validation for dengue and other acute febrile illness
|
|---|---|
| Published in |
Frontiers in Digital Health, February 2023
|
| DOI | 10.3389/fdgth.2023.1057467 |
| Pubmed ID | |
| Authors |
Bernard Hernandez, Oliver Stiff, Damien K. Ming, Chanh Ho Quang, Vuong Nguyen Lam, Tuan Nguyen Minh, Chau Nguyen Van Vinh, Nguyet Nguyen Minh, Huy Nguyen Quang, Lam Phung Khanh, Tam Dong Thi Hoai, Trung Dinh The, Trieu Huynh Trung, Bridget Wills, Cameron P. Simmons, Alison H. Holmes, Sophie Yacoub, Pantelis Georgiou, on behalf of the Vietnam ICU Translational Applications Laboratory investigators |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 13% |
| Switzerland | 1 | 13% |
| Unknown | 6 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 88% |
| Science communicators (journalists, bloggers, editors) | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 11 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 27% |
| Student > Doctoral Student | 2 | 18% |
| Student > Ph. D. Student | 1 | 9% |
| Student > Master | 1 | 9% |
| Unknown | 4 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 2 | 18% |
| Engineering | 2 | 18% |
| Agricultural and Biological Sciences | 1 | 9% |
| Business, Management and Accounting | 1 | 9% |
| Unknown | 5 | 45% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 14 March 2023.
All research outputs
#14,830,228
of 25,732,188 outputs
Outputs from Frontiers in Digital Health
#379
of 856 outputs
Outputs of similar age
#176,648
of 428,274 outputs
Outputs of similar age from Frontiers in Digital Health
#26
of 61 outputs
Altmetric has tracked 25,732,188 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 856 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.8. This one has gotten more attention than average, scoring higher than 53% 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 428,274 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 57% of its contemporaries.
We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 57% of its contemporaries.