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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep learning model for classifying endometrial lesions
|
|---|---|
| Published in |
Journal of Translational Medicine, January 2021
|
| DOI | 10.1186/s12967-020-02660-x |
| Pubmed ID | |
| Authors |
YunZheng Zhang, ZiHao Wang, Jin Zhang, CuiCui Wang, YuShan Wang, Hao Chen, LuHe Shan, JiaNing Huo, JiaHui Gu, Xiaoxin Ma |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 54 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 5 | 9% |
| Researcher | 4 | 7% |
| Unspecified | 3 | 6% |
| Other | 3 | 6% |
| Student > Doctoral Student | 2 | 4% |
| Other | 8 | 15% |
| Unknown | 29 | 54% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 7 | 13% |
| Engineering | 5 | 9% |
| Computer Science | 5 | 9% |
| Unspecified | 3 | 6% |
| Biochemistry, Genetics and Molecular Biology | 3 | 6% |
| Other | 2 | 4% |
| Unknown | 29 | 54% |
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 17 February 2021.
All research outputs
#18,116,235
of 23,271,751 outputs
Outputs from Journal of Translational Medicine
#2,815
of 4,103 outputs
Outputs of similar age
#356,395
of 503,379 outputs
Outputs of similar age from Journal of Translational Medicine
#65
of 95 outputs
Altmetric has tracked 23,271,751 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,103 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one is in the 26th percentile – i.e., 26% 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 503,379 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 95 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.