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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Automated quantitative analysis of Ki-67 staining and HE images recognition and registration based on whole tissue sections in breast carcinoma
|
|---|---|
| Published in |
Diagnostic Pathology, May 2020
|
| DOI | 10.1186/s13000-020-00957-5 |
| Pubmed ID | |
| Authors |
Min Feng, Yang Deng, Libo Yang, Qiuyang Jing, Zhang Zhang, Lian Xu, Xiaoxia Wei, Yanyan Zhou, Diwei Wu, Fei Xiang, Yizhe Wang, Ji Bao, Hong Bu |
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 States | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 71 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 13% |
| Researcher | 7 | 10% |
| Student > Bachelor | 5 | 7% |
| Professor > Associate Professor | 4 | 6% |
| Student > Master | 4 | 6% |
| Other | 11 | 15% |
| Unknown | 31 | 44% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 10 | 14% |
| Medicine and Dentistry | 10 | 14% |
| Engineering | 6 | 8% |
| Biochemistry, Genetics and Molecular Biology | 3 | 4% |
| Unspecified | 3 | 4% |
| Other | 8 | 11% |
| Unknown | 31 | 44% |
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 07 June 2020.
All research outputs
#14,484,106
of 23,211,181 outputs
Outputs from Diagnostic Pathology
#429
of 1,145 outputs
Outputs of similar age
#221,219
of 396,626 outputs
Outputs of similar age from Diagnostic Pathology
#6
of 22 outputs
Altmetric has tracked 23,211,181 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,145 research outputs from this source. They receive a mean Attention Score of 2.8. This one has gotten more attention than average, scoring higher than 57% 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 396,626 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 22 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 63% of its contemporaries.