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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Development of diagnostic algorithm using machine learning for distinguishing between active tuberculosis and latent tuberculosis infection
|
|---|---|
| Published in |
BMC Infectious Diseases, December 2022
|
| DOI | 10.1186/s12879-022-07954-7 |
| Pubmed ID | |
| Authors |
Ying Luo, Ying Xue, Wei Liu, Huijuan Song, Yi Huang, Guoxing Tang, Feng Wang, Qi Wang, Yimin Cai, Ziyong Sun |
X Demographics
The data shown below were collected from the profiles of 9 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 | 22% |
| United Kingdom | 2 | 22% |
| Mexico | 1 | 11% |
| Unknown | 4 | 44% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 78% |
| Scientists | 2 | 22% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 22 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 3 | 14% |
| Researcher | 2 | 9% |
| Lecturer | 2 | 9% |
| Student > Ph. D. Student | 2 | 9% |
| Student > Bachelor | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 11 | 50% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 5 | 23% |
| Medicine and Dentistry | 3 | 14% |
| Biochemistry, Genetics and Molecular Biology | 1 | 5% |
| Social Sciences | 1 | 5% |
| Engineering | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 11 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 January 2023.
All research outputs
#2,319,174
of 23,885,338 outputs
Outputs from BMC Infectious Diseases
#677
of 8,002 outputs
Outputs of similar age
#47,001
of 437,712 outputs
Outputs of similar age from BMC Infectious Diseases
#16
of 149 outputs
Altmetric has tracked 23,885,338 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 8,002 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. 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 437,712 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 89% of its contemporaries.
We're also able to compare this research output to 149 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.