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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Machine learning approaches for the genomic prediction of rheumatoid arthritis and systemic lupus erythematosus
|
|---|---|
| Published in |
BioData Mining, December 2021
|
| DOI | 10.1186/s13040-021-00284-5 |
| Pubmed ID | |
| Authors |
Chih-Wei Chung, Tzu-Hung Hsiao, Chih-Jen Huang, Yen-Ju Chen, Hsin-Hua Chen, Ching-Heng Lin, Seng-Cho Chou, Tzer-Shyong Chen, Yu-Fang Chung, Hwai-I Yang, Yi-Ming Chen |
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 % |
|---|---|---|
| United Kingdom | 2 | 67% |
| United States | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 31 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 5 | 16% |
| Researcher | 4 | 13% |
| Student > Ph. D. Student | 4 | 13% |
| Student > Bachelor | 2 | 6% |
| Lecturer > Senior Lecturer | 1 | 3% |
| Other | 2 | 6% |
| Unknown | 13 | 42% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 4 | 13% |
| Biochemistry, Genetics and Molecular Biology | 2 | 6% |
| Agricultural and Biological Sciences | 2 | 6% |
| Mathematics | 1 | 3% |
| Business, Management and Accounting | 1 | 3% |
| Other | 4 | 13% |
| Unknown | 17 | 55% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 December 2021.
All research outputs
#15,255,201
of 22,684,168 outputs
Outputs from BioData Mining
#225
of 307 outputs
Outputs of similar age
#274,505
of 496,444 outputs
Outputs of similar age from BioData Mining
#3
of 5 outputs
Altmetric has tracked 22,684,168 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 307 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one is in the 19th percentile – i.e., 19% of its peers scored the same or lower than it.
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 496,444 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.