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Automated quantitative analysis of Ki-67 staining and HE images recognition and registration based on whole tissue sections in breast carcinoma

Overview of attention for article published in Diagnostic Pathology, May 2020
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  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

twitter
3 X users

Citations

dimensions_citation
28 Dimensions

Readers on

mendeley
69 Mendeley
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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

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 69 100%

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 9 13%
Unknown 31 45%
Readers by discipline Count As %
Computer Science 10 14%
Medicine and Dentistry 10 14%
Engineering 6 9%
Biochemistry, Genetics and Molecular Biology 3 4%
Business, Management and Accounting 1 1%
Other 8 12%
Unknown 31 45%
Attention Score in Context

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.