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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A Machine Learning Model to Predict the Triple Negative Breast Cancer Immune Subtype
|
|---|---|
| Published in |
Frontiers in immunology, September 2021
|
| DOI | 10.3389/fimmu.2021.749459 |
| Pubmed ID | |
| Authors |
Zihao Chen, Maoli Wang, Rudy Leon De Wilde, Ruifa Feng, Mingqiang Su, Luz Angela Torres-de la Roche, Wenjie Shi |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 5 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 68 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 10% |
| Unspecified | 6 | 9% |
| Student > Bachelor | 3 | 4% |
| Student > Master | 3 | 4% |
| Student > Ph. D. Student | 3 | 4% |
| Other | 7 | 10% |
| Unknown | 39 | 57% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 6 | 9% |
| Medicine and Dentistry | 6 | 9% |
| Computer Science | 6 | 9% |
| Biochemistry, Genetics and Molecular Biology | 4 | 6% |
| Engineering | 2 | 3% |
| Other | 5 | 7% |
| Unknown | 39 | 57% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 04 October 2021.
All research outputs
#16,274,398
of 26,163,973 outputs
Outputs from Frontiers in immunology
#15,920
of 33,003 outputs
Outputs of similar age
#225,282
of 440,380 outputs
Outputs of similar age from Frontiers in immunology
#707
of 1,387 outputs
Altmetric has tracked 26,163,973 research outputs across all sources so far. This one is in the 36th percentile – i.e., 36% of other outputs scored the same or lower than it.
So far Altmetric has tracked 33,003 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.5. This one is in the 48th percentile – i.e., 48% 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 440,380 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,387 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.