| Title |
Machine Learning-Based Decision Model to Distinguish Between COVID-19 and Influenza: A Retrospective, Two-Centered, Diagnostic Study
|
|---|---|
| Published in |
Risk Management and Healthcare Policy, February 2021
|
| DOI | 10.2147/rmhp.s291498 |
| Pubmed ID | |
| Authors |
Xianlong Zhou, Zhichao Wang, Shaoping Li, Tanghai Liu, Xiaolin Wang, Jian Xia, Yan Zhao |
X Demographics
The data shown below were collected from the profiles of 4 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 | 2 | 50% |
| Netherlands | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 38 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 13% |
| Student > Postgraduate | 5 | 13% |
| Researcher | 3 | 8% |
| Student > Doctoral Student | 3 | 8% |
| Professor > Associate Professor | 3 | 8% |
| Other | 9 | 24% |
| Unknown | 10 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 8 | 21% |
| Nursing and Health Professions | 4 | 11% |
| Computer Science | 4 | 11% |
| Arts and Humanities | 2 | 5% |
| Immunology and Microbiology | 1 | 3% |
| Other | 8 | 21% |
| Unknown | 11 | 29% |
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 24 February 2021.
All research outputs
#14,304,827
of 24,417,958 outputs
Outputs from Risk Management and Healthcare Policy
#272
of 694 outputs
Outputs of similar age
#246,451
of 514,622 outputs
Outputs of similar age from Risk Management and Healthcare Policy
#19
of 57 outputs
Altmetric has tracked 24,417,958 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 694 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.7. This one has gotten more attention than average, scoring higher than 60% 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 514,622 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 51% of its contemporaries.
We're also able to compare this research output to 57 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 68% of its contemporaries.