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A Deep Learning Model for the Automatic Recognition of Aplastic Anemia, Myelodysplastic Syndromes, and Acute Myeloid Leukemia Based on Bone Marrow Smear

Overview of attention for article published in Frontiers in oncology, April 2022
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

Mentioned by

twitter
1 X user

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
18 Mendeley
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Title
A Deep Learning Model for the Automatic Recognition of Aplastic Anemia, Myelodysplastic Syndromes, and Acute Myeloid Leukemia Based on Bone Marrow Smear
Published in
Frontiers in oncology, April 2022
DOI 10.3389/fonc.2022.844978
Pubmed ID
Authors

Meifang Wang, Chunxia Dong, Yan Gao, Jianlan Li, Mengru Han, Lijun Wang

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 11%
Researcher 2 11%
Librarian 1 6%
Professor 1 6%
Unknown 12 67%
Readers by discipline Count As %
Unspecified 2 11%
Biochemistry, Genetics and Molecular Biology 1 6%
Engineering 1 6%
Unknown 14 78%
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 02 May 2022.
All research outputs
#17,301,727
of 25,392,582 outputs
Outputs from Frontiers in oncology
#8,039
of 22,436 outputs
Outputs of similar age
#268,582
of 447,085 outputs
Outputs of similar age from Frontiers in oncology
#561
of 1,555 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,436 research outputs from this source. They receive a mean Attention Score of 3.0. This one has gotten more attention than average, scoring higher than 58% 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 447,085 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,555 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 59% of its contemporaries.