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MSAL-Net: improve accurate segmentation of nuclei in histopathology images by multiscale attention learning network

Overview of attention for article published in BMC Medical Informatics and Decision Making, April 2022
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  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 X users

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
13 Mendeley
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Title
MSAL-Net: improve accurate segmentation of nuclei in histopathology images by multiscale attention learning network
Published in
BMC Medical Informatics and Decision Making, April 2022
DOI 10.1186/s12911-022-01826-5
Pubmed ID
Authors

Haider Ali, Imran ul Haq, Lei Cui, Jun Feng

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Librarian 1 8%
Lecturer 1 8%
Student > Doctoral Student 1 8%
Student > Bachelor 1 8%
Researcher 1 8%
Other 0 0%
Unknown 8 62%
Readers by discipline Count As %
Computer Science 1 8%
Medicine and Dentistry 1 8%
Engineering 1 8%
Unknown 10 77%
Attention Score in Context

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 05 April 2022.
All research outputs
#15,867,545
of 23,577,761 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,343
of 2,027 outputs
Outputs of similar age
#253,055
of 444,293 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#29
of 55 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,027 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 24th percentile – i.e., 24% 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 444,293 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.