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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Predict Ki-67 Positive Cells in H&E-Stained Images Using Deep Learning Independently From IHC-Stained Images
|
|---|---|
| Published in |
Frontiers in Molecular Biosciences, August 2020
|
| DOI | 10.3389/fmolb.2020.00183 |
| Pubmed ID | |
| Authors |
Yiqing Liu, Xi Li, Aiping Zheng, Xihan Zhu, Shuting Liu, Mengying Hu, Qianjiang Luo, Huina Liao, Mubiao Liu, Yonghong He, Yupeng Chen |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Philippines | 1 | 20% |
| Unknown | 4 | 80% |
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 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 50 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 16% |
| Student > Ph. D. Student | 7 | 14% |
| Student > Bachelor | 5 | 10% |
| Student > Master | 4 | 8% |
| Other | 3 | 6% |
| Other | 2 | 4% |
| Unknown | 21 | 42% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 7 | 14% |
| Computer Science | 7 | 14% |
| Medicine and Dentistry | 5 | 10% |
| Biochemistry, Genetics and Molecular Biology | 5 | 10% |
| Neuroscience | 2 | 4% |
| Other | 2 | 4% |
| Unknown | 22 | 44% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 20 August 2021.
All research outputs
#7,432,670
of 23,577,761 outputs
Outputs from Frontiers in Molecular Biosciences
#722
of 4,107 outputs
Outputs of similar age
#156,756
of 400,237 outputs
Outputs of similar age from Frontiers in Molecular Biosciences
#30
of 122 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 4,107 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done well, scoring higher than 82% 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 400,237 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.
We're also able to compare this research output to 122 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.